{"about":{"non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","site":"https://codewithpapers.app","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page","syntology":{"site":"https://syntology.ai","developers":"https://syntology.ai/developers","mcp":{"server":"https://syntology.ai/mcp","transport":"streamable-http","server_card":"https://syntology.ai/.well-known/mcp/server-card.json","auth":{"type":"trial token, no account","trial_token":"https://syntology.ai/api/oauth/trial/token","method":"POST","docs":"https://syntology.ai/developers"}},"have":"https://syntology.ai/api/graph/have?x=<method, arXiv id or title> (free, answers coverage only)","paper_base":"https://syntology.ai/paper/","atlas_base":"https://app.syntology.ai/?focus="},"machine_readable":[{"url":"https://codewithpapers.app/llms.txt","what":"the machine catalog: every machine-readable file, counted"},{"url":"https://codewithpapers.app/index/manifest.json","what":"paper-to-code index by arXiv id, with Syntology's counts"},{"url":"https://codewithpapers.app/search/manifest.json","what":"site search index (titles, authors) and its files"},{"url":"https://codewithpapers.app/download","what":"bulk files: Syntology's layer, described there"},{"url":"https://codewithpapers.app/build_manifest.json","what":"the build record: inputs, counts, exclusions, probes"}]},"url":"/task/depth-estimation/papers/17","list_of":"/task/depth-estimation","task":"Depth Estimation","archive":{"snapshot":"2025-07-28"},"key_notes":{"n_ran_checked":"legacy name, kept unchanged so existing readers do not break: it counts the samples that ran with no instrument failure (honoured, violated, and ran with no contract checked); it does not mean a contract was checked, and the pages print it as 'K with no instrument failure', not 'K checked'","n_constructed":"a sub-count of the samples that ran, never subtracted from them and never a failure: an executed sample whose run returned an instance of its own class (fixture_out_type equals the entry name): the run built an object and did not compute a result (Syntology's RAN record, counts.constructed)"},"syntology_read_at":"2026-09-28T10:30:06+00:00","order":"archive","order_definition":"repositories listed in the archive (most first), then date (newest first), then slug","page":17,"pages_in_order":25,"rows_per_page":100,"rows":[1601,1700],"of":2454,"counts":{"archive_papers_tagged":2454,"with_a_code_link":1029,"where_syntology_ran_a_sample":292,"not_listed_spam_title":0,"listed":2454,"listed_where_code_ran":292,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":260,"every_run_a_failure_of_syntologys_instrument":32,"listed_with_a_run_with_no_instrument_failure":260,"listed_every_run_a_failure_of_syntologys_instrument":32,"filter":{"states":["a run with no instrument failure","any run, instrument failures included"],"default":"a run with no instrument failure","note":"on the 'only where code ran' pages the default hides, in the browser, the rows where every run was a failure of Syntology's instrument; the second state shows them again. Rows are hidden, never re-ordered; these twins list every row"}},"definition":"distinct papers the archive tags; 'where Syntology ran a sample' counts papers with at least one harvested sample that ran, which is not a correctness claim"},"first_page":"/task/depth-estimation","prev":"/task/depth-estimation/papers/16","next":"/task/depth-estimation/papers/18","papers":[{"url":null,"slug":"multi-object-discovery-by-low-dimensional","title":"Multi-Object Discovery by Low-Dimensional Object Motion","date":"2023-07-16","arxiv_id":"2307.08027","repositories_listed":0,"syntology":null},{"url":null,"slug":"raymvsnet-learning-ray-based-1d-implicit-1","title":"RayMVSNet++: Learning Ray-based 1D Implicit Fields for Accurate Multi-View Stereo","date":"2023-07-16","arxiv_id":"2307.10233","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-subjective-time-series-data-via","title":"Learning Subjective Time-Series Data via Utopia Label Distribution Approximation","date":"2023-07-15","arxiv_id":"2307.07682","repositories_listed":0,"syntology":null},{"url":null,"slug":"transpose-a-transformer-based-6d-object-pose","title":"TransPose: A Transformer-based 6D Object Pose Estimation Network with Depth Refinement","date":"2023-07-09","arxiv_id":"2307.05561","repositories_listed":0,"syntology":null},{"url":null,"slug":"depth-estimation-analysis-of-orthogonally","title":"Depth Estimation Analysis of Orthogonally Divergent Fisheye Cameras with Distortion Removal","date":"2023-07-07","arxiv_id":"2307.03602","repositories_listed":0,"syntology":null},{"url":null,"slug":"svdm-single-view-diffusion-model-for-pseudo","title":"SVDM: Single-View Diffusion Model for Pseudo-Stereo 3D Object Detection","date":"2023-07-05","arxiv_id":"2307.02270","repositories_listed":0,"syntology":null},{"url":"/paper/lxl-lidar-exclusive-lean-3d-object-detection","slug":"lxl-lidar-exclusive-lean-3d-object-detection","title":"LXL: LiDAR Excluded Lean 3D Object Detection with 4D Imaging Radar and Camera Fusion","date":"2023-07-03","arxiv_id":"2307.00724","repositories_listed":0,"syntology":null},{"url":null,"slug":"gmm-delving-into-gradient-aware-and-model","title":"GMM: Delving into Gradient Aware and Model Perceive Depth Mining for Monocular 3D Detection","date":"2023-06-30","arxiv_id":"2306.17450","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-360-circ-structured-light-with-learned","title":"Neural 360$^\\circ$ Structured Light with Learned Metasurfaces","date":"2023-06-23","arxiv_id":"2306.13361","repositories_listed":0,"syntology":null},{"url":null,"slug":"continuous-online-extrinsic-calibration-of","title":"Continuous Online Extrinsic Calibration of Fisheye Camera and LiDAR","date":"2023-06-22","arxiv_id":"2306.13240","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-at-a-time-multi-step-volumetric","title":"One at a Time: Progressive Multi-step Volumetric Probability Learning for Reliable 3D Scene Perception","date":"2023-06-22","arxiv_id":"2306.12681","repositories_listed":0,"syntology":null},{"url":null,"slug":"bevscope-enhancing-self-supervised-depth","title":"BEVScope: Enhancing Self-Supervised Depth Estimation Leveraging Bird's-Eye-View in Dynamic Scenarios","date":"2023-06-20","arxiv_id":"2306.11598","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-multi-task-learning-framework","title":"Self-supervised Multi-task Learning Framework for Safety and Health-Oriented Connected Driving Environment Perception using Onboard Camera","date":"2023-06-20","arxiv_id":"2306.11822","repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-depth-map-progressively","title":"Understanding Depth Map Progressively: Adaptive Distance Interval Separation for Monocular 3d Object Detection","date":"2023-06-19","arxiv_id":"2306.10921","repositories_listed":0,"syntology":null},{"url":null,"slug":"c2f2neus-cascade-cost-frustum-fusion-for-high","title":"C2F2NeUS: Cascade Cost Frustum Fusion for High Fidelity and Generalizable Neural Surface Reconstruction","date":"2023-06-16","arxiv_id":"2306.10003","repositories_listed":0,"syntology":null},{"url":null,"slug":"simplemapping-real-time-visual-inertial-dense","title":"SimpleMapping: Real-Time Visual-Inertial Dense Mapping with Deep Multi-View Stereo","date":"2023-06-14","arxiv_id":"2306.08648","repositories_listed":0,"syntology":null},{"url":null,"slug":"lightweight-monocular-depth-estimation-via","title":"Lightweight Monocular Depth Estimation via Token-Sharing Transformer","date":"2023-06-09","arxiv_id":"2306.05682","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dynamic-feature-interaction-framework-for","title":"A Dynamic Feature Interaction Framework for Multi-task Visual Perception","date":"2023-06-08","arxiv_id":"2306.05061","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-stage-3d-geometry-preserving-depth-1","title":"Single-Stage 3D Geometry-Preserving Depth Estimation Model Training on Dataset Mixtures with Uncalibrated Stereo Data","date":"2023-06-05","arxiv_id":"2306.02878","repositories_listed":0,"syntology":null},{"url":null,"slug":"panogrf-generalizable-spherical-radiance","title":"PanoGRF: Generalizable Spherical Radiance Fields for Wide-baseline Panoramas","date":"2023-06-02","arxiv_id":"2306.01531","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-surprising-effectiveness-of-diffusion","title":"The Surprising Effectiveness of Diffusion Models for Optical Flow and Monocular Depth Estimation","date":"2023-06-02","arxiv_id":"2306.01923","repositories_listed":0,"syntology":null},{"url":null,"slug":"usim-dal-uncertainty-aware-statistical-image","title":"USIM-DAL: Uncertainty-aware Statistical Image Modeling-based Dense Active Learning for Super-resolution","date":"2023-05-27","arxiv_id":"2305.17520","repositories_listed":0,"syntology":null},{"url":null,"slug":"simhaze-game-engine-simulated-data-for-real","title":"SimHaze: game engine simulated data for real-world dehazing","date":"2023-05-25","arxiv_id":"2305.16481","repositories_listed":0,"syntology":null},{"url":null,"slug":"autodepthnet-high-frame-rate-depth-map","title":"AutoDepthNet: High Frame Rate Depth Map Reconstruction using Commodity Depth and RGB Cameras","date":"2023-05-24","arxiv_id":"2305.14731","repositories_listed":0,"syntology":null},{"url":"/paper/polarimetric-imaging-for-perception","slug":"polarimetric-imaging-for-perception","title":"Polarimetric Imaging for Perception","date":"2023-05-24","arxiv_id":"2305.14787","repositories_listed":0,"syntology":null},{"url":null,"slug":"fedora-flying-event-dataset-for-reactive","title":"FEDORA: Flying Event Dataset fOr Reactive behAvior","date":"2023-05-22","arxiv_id":"2305.14392","repositories_listed":0,"syntology":null},{"url":null,"slug":"gated-stereo-joint-depth-estimation-from-1","title":"Gated Stereo: Joint Depth Estimation from Gated and Wide-Baseline Active Stereo Cues","date":"2023-05-22","arxiv_id":"2305.12955","repositories_listed":0,"syntology":null},{"url":null,"slug":"panelnet-understanding-360-indoor-environment","title":"PanelNet: Understanding 360 Indoor Environment via Panel Representation","date":"2023-05-16","arxiv_id":"2305.09078","repositories_listed":0,"syntology":null},{"url":null,"slug":"metamorphosis-task-oriented-privacy-cognizant","title":"MetaMorphosis: Task-oriented Privacy Cognizant Feature Generation for Multi-task Learning","date":"2023-05-13","arxiv_id":"2305.07815","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-monocular-depth-in-dynamic","title":"Learning Monocular Depth in Dynamic Environment via Context-aware Temporal Attention","date":"2023-05-12","arxiv_id":"2305.07397","repositories_listed":0,"syntology":null},{"url":null,"slug":"meta-optimization-for-higher-model","title":"Meta-Optimization for Higher Model Generalizability in Single-Image Depth Prediction","date":"2023-05-12","arxiv_id":"2305.07269","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-multi-modal-approach-to-single-modal-visual","title":"A Multi-modal Approach to Single-modal Visual Place Classification","date":"2023-05-10","arxiv_id":"2305.06179","repositories_listed":0,"syntology":null},{"url":null,"slug":"fusiondepth-complement-self-supervised","title":"FusionDepth: Complement Self-Supervised Monocular Depth Estimation with Cost Volume","date":"2023-05-10","arxiv_id":"2305.06036","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-2d-face-recognition-via-fine-level","title":"Improving 2D face recognition via fine-level facial depth generation and RGB-D complementary feature learning","date":"2023-05-08","arxiv_id":"2305.04426","repositories_listed":0,"syntology":null},{"url":null,"slug":"edge-aware-consistent-stereo-video-depth","title":"Edge-aware Consistent Stereo Video Depth Estimation","date":"2023-05-04","arxiv_id":"2305.02645","repositories_listed":0,"syntology":null},{"url":null,"slug":"high-resolution-synthetic-rgb-d-datasets-for","title":"High-Resolution Synthetic RGB-D Datasets for Monocular Depth Estimation","date":"2023-05-02","arxiv_id":"2305.01732","repositories_listed":0,"syntology":null},{"url":null,"slug":"depth-relative-self-attention-for-monocular","title":"Depth-Relative Self Attention for Monocular Depth Estimation","date":"2023-04-25","arxiv_id":"2304.12849","repositories_listed":0,"syntology":null},{"url":null,"slug":"fsnet-redesign-self-supervised-monodepth-for","title":"FSNet: Redesign Self-Supervised MonoDepth for Full-Scale Depth Prediction for Autonomous Driving","date":"2023-04-21","arxiv_id":"2304.10719","repositories_listed":0,"syntology":null},{"url":null,"slug":"crossfusion-interleaving-cross-modal","title":"CrossFusion: Interleaving Cross-modal Complementation for Noise-resistant 3D Object Detection","date":"2023-04-19","arxiv_id":"2304.09694","repositories_listed":0,"syntology":null},{"url":null,"slug":"darswin-distortion-aware-radial-swin","title":"DarSwin: Distortion Aware Radial Swin Transformer","date":"2023-04-19","arxiv_id":"2304.09691","repositories_listed":0,"syntology":null},{"url":null,"slug":"360-circ-high-resolution-depth-estimation-via","title":"360$^\\circ$ High-Resolution Depth Estimation via Uncertainty-aware Structural Knowledge Transfer","date":"2023-04-17","arxiv_id":"2304.07967","repositories_listed":0,"syntology":null},{"url":null,"slug":"egformer-equirectangular-geometry-biased","title":"EGformer: Equirectangular Geometry-biased Transformer for 360 Depth Estimation","date":"2023-04-16","arxiv_id":"2304.07803","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-second-monocular-depth-estimation","title":"The Second Monocular Depth Estimation Challenge","date":"2023-04-14","arxiv_id":"2304.07051","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-based-tracking-of-human-hands","title":"Event-based tracking of human hands","date":"2023-04-13","arxiv_id":"2304.06534","repositories_listed":0,"syntology":null},{"url":null,"slug":"bevstereo-accurate-depth-estimation-in-multi","title":"BEVStereo++: Accurate Depth Estimation in Multi-view 3D Object Detection via Dynamic Temporal Stereo","date":"2023-04-09","arxiv_id":"2304.04185","repositories_listed":0,"syntology":null},{"url":null,"slug":"delira-self-supervised-depth-light-and","title":"DeLiRa: Self-Supervised Depth, Light, and Radiance Fields","date":"2023-04-06","arxiv_id":"2304.02797","repositories_listed":0,"syntology":null},{"url":null,"slug":"ega-depth-efficient-guided-attention-for-self","title":"EGA-Depth: Efficient Guided Attention for Self-Supervised Multi-Camera Depth Estimation","date":"2023-04-06","arxiv_id":"2304.03369","repositories_listed":0,"syntology":null},{"url":null,"slug":"semhint-md-learning-from-noisy-semantic","title":"SemHint-MD: Learning from Noisy Semantic Labels for Self-Supervised Monocular Depth Estimation","date":"2023-03-31","arxiv_id":"2303.18219","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-image-depth-prediction-made-better-a","title":"Single Image Depth Prediction Made Better: A Multivariate Gaussian Take","date":"2023-03-31","arxiv_id":"2303.18164","repositories_listed":0,"syntology":null},{"url":null,"slug":"tidy-psfs-computational-imaging-with-time","title":"TiDy-PSFs: Computational Imaging with Time-Averaged Dynamic Point-Spread-Functions","date":"2023-03-30","arxiv_id":"2303.17583","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-frame-self-supervised-depth-estimation","title":"Multi-Frame Self-Supervised Depth Estimation with Multi-Scale Feature Fusion in Dynamic Scenes","date":"2023-03-26","arxiv_id":"2303.14628","repositories_listed":0,"syntology":null},{"url":null,"slug":"mogde-boosting-mobile-monocular-3d-object","title":"MoGDE: Boosting Mobile Monocular 3D Object Detection with Ground Depth Estimation","date":"2023-03-23","arxiv_id":"2303.13561","repositories_listed":0,"syntology":null},{"url":null,"slug":"scade-nerfs-from-space-carving-with-ambiguity","title":"SCADE: NeRFs from Space Carving with Ambiguity-Aware Depth Estimates","date":"2023-03-23","arxiv_id":"2303.13582","repositories_listed":0,"syntology":null},{"url":null,"slug":"hrdfuse-monocular-360degdepth-estimation-by","title":"HRDFuse: Monocular 360°Depth Estimation by Collaboratively Learning Holistic-with-Regional Depth Distributions","date":"2023-03-21","arxiv_id":"2303.11616","repositories_listed":0,"syntology":null},{"url":null,"slug":"boosting-weakly-supervised-object-detection-2","title":"Boosting Weakly Supervised Object Detection using Fusion and Priors from Hallucinated Depth","date":"2023-03-20","arxiv_id":"2303.10937","repositories_listed":0,"syntology":null},{"url":null,"slug":"versatile-depth-estimator-based-on-common","title":"Versatile Depth Estimator Based on Common Relative Depth Estimation and Camera-Specific Relative-to-Metric Depth Conversion","date":"2023-03-20","arxiv_id":"2303.10991","repositories_listed":0,"syntology":null},{"url":null,"slug":"spectrum-inspired-low-light-image-translation","title":"Spectrum-inspired Low-light Image Translation for Saliency Detection","date":"2023-03-17","arxiv_id":"2303.10145","repositories_listed":0,"syntology":null},{"url":null,"slug":"cross-dimensional-refined-learning-for-real","title":"Cross-Dimensional Refined Learning for Real-Time 3D Visual Perception from Monocular Video","date":"2023-03-16","arxiv_id":"2303.09248","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-simple-baseline-for-supervised-surround","title":"A Simple Baseline for Supervised Surround-view Depth Estimation","date":"2023-03-14","arxiv_id":"2303.07759","repositories_listed":0,"syntology":null},{"url":null,"slug":"one-scalar-is-all-you-need-absolute-depth","title":"Do More With What You Have: Transferring Depth-Scale from Labeled to Unlabeled Domains","date":"2023-03-14","arxiv_id":"2303.07662","repositories_listed":0,"syntology":null},{"url":null,"slug":"dehrformer-real-time-transformer-for-depth","title":"DEHRFormer: Real-time Transformer for Depth Estimation and Haze Removal from Varicolored Haze Scenes","date":"2023-03-13","arxiv_id":"2303.06905","repositories_listed":0,"syntology":null},{"url":null,"slug":"discovering-multiple-algorithm-configurations","title":"Discovering Multiple Algorithm Configurations","date":"2023-03-13","arxiv_id":"2303.07434","repositories_listed":0,"syntology":null},{"url":null,"slug":"evconv-fast-cnn-inference-on-event-camera","title":"EvConv: Fast CNN Inference on Event Camera Inputs For High-Speed Robot Perception","date":"2023-03-08","arxiv_id":"2303.04670","repositories_listed":0,"syntology":null},{"url":null,"slug":"dwinformer-dual-window-transformers-for-end","title":"DwinFormer: Dual Window Transformers for End-to-End Monocular Depth Estimation","date":"2023-03-06","arxiv_id":"2303.02968","repositories_listed":0,"syntology":null},{"url":null,"slug":"towards-domain-generalization-for-multi-view","title":"Towards Domain Generalization for Multi-view 3D Object Detection in Bird-Eye-View","date":"2023-03-03","arxiv_id":"2303.01686","repositories_listed":0,"syntology":null},{"url":null,"slug":"aparate-adaptive-adversarial-patch-for-cnn","title":"APARATE: Adaptive Adversarial Patch for CNN-based Monocular Depth Estimation for Autonomous Navigation","date":"2023-03-02","arxiv_id":"2303.01351","repositories_listed":0,"syntology":null},{"url":null,"slug":"dejavu-conditional-regenerative-learning-to","title":"DejaVu: Conditional Regenerative Learning to Enhance Dense Prediction","date":"2023-03-02","arxiv_id":"2303.01573","repositories_listed":0,"syntology":null},{"url":null,"slug":"i2p-rec-recognizing-images-on-large-scale","title":"I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird's Eye View Projections","date":"2023-03-02","arxiv_id":"2303.01043","repositories_listed":0,"syntology":null},{"url":null,"slug":"stdepthformer-predicting-spatio-temporal","title":"STDepthFormer: Predicting Spatio-temporal Depth from Video with a Self-supervised Transformer Model","date":"2023-03-02","arxiv_id":"2303.01196","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-estimate-two-dense-depths-from","title":"Learning to Estimate Two Dense Depths from LiDAR and Event Data","date":"2023-02-28","arxiv_id":"2302.14444","repositories_listed":0,"syntology":null},{"url":"/paper/monocular-depth-estimation-using-diffusion","slug":"monocular-depth-estimation-using-diffusion","title":"Monocular Depth Estimation using Diffusion Models","date":"2023-02-28","arxiv_id":"2302.14816","repositories_listed":0,"syntology":null},{"url":null,"slug":"mvtrans-multi-view-perception-of-transparent","title":"MVTrans: Multi-View Perception of Transparent Objects","date":"2023-02-22","arxiv_id":"2302.11683","repositories_listed":0,"syntology":null},{"url":null,"slug":"bokeh-rendering-based-on-adaptive-depth","title":"Bokeh Rendering Based on Adaptive Depth Calibration Network","date":"2023-02-21","arxiv_id":"2302.10808","repositories_listed":0,"syntology":null},{"url":null,"slug":"depth-estimation-and-image-restoration-by","title":"Depth Estimation and Image Restoration by Deep Learning from Defocused Images","date":"2023-02-21","arxiv_id":"2302.10730","repositories_listed":0,"syntology":null},{"url":"/paper/learning-3d-photography-videos-via-self","slug":"learning-3d-photography-videos-via-self","title":"Learning 3D Photography Videos via Self-supervised Diffusion on Single Images","date":"2023-02-21","arxiv_id":"2302.10781","repositories_listed":0,"syntology":null},{"url":null,"slug":"monopgc-monocular-3d-object-detection-with","title":"MonoPGC: Monocular 3D Object Detection with Pixel Geometry Contexts","date":"2023-02-21","arxiv_id":"2302.10549","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-evaluation-of-deep-learning-models-for","title":"An evaluation of deep learning models for predicting water depth evolution in urban floods","date":"2023-02-20","arxiv_id":"2302.10062","repositories_listed":0,"syntology":null},{"url":null,"slug":"glocalfuse-depth-fusing-transformers-and-cnns","title":"GlocalFuse-Depth: Fusing Transformers and CNNs for All-day Self-supervised Monocular Depth Estimation","date":"2023-02-20","arxiv_id":"2302.09884","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-the-metrics-for-evaluating-monocular-depth","title":"On the Metrics for Evaluating Monocular Depth Estimation","date":"2023-02-20","arxiv_id":"2302.10007","repositories_listed":0,"syntology":null},{"url":null,"slug":"long-range-object-level-monocular-depth","title":"Long Range Object-Level Monocular Depth Estimation for UAVs","date":"2023-02-17","arxiv_id":"2302.08943","repositories_listed":0,"syntology":null},{"url":null,"slug":"spectral-3d-computer-vision-a-review","title":"Spectral 3D Computer Vision -- A Review","date":"2023-02-16","arxiv_id":"2302.08054","repositories_listed":0,"syntology":null},{"url":null,"slug":"even-an-event-based-framework-for-monocular","title":"EVEN: An Event-Based Framework for Monocular Depth Estimation at Adverse Night Conditions","date":"2023-02-08","arxiv_id":"2302.03860","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-disparity-refinement-framework-for-learning","title":"A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images","date":"2023-02-05","arxiv_id":"2302.02294","repositories_listed":0,"syntology":null},{"url":null,"slug":"multi-task-self-supervised-learning-for-image","title":"Multi-Task Self-Supervised Learning for Image Segmentation Task","date":"2023-02-05","arxiv_id":"2302.02483","repositories_listed":0,"syntology":null},{"url":null,"slug":"scenescape-text-driven-consistent-scene-1","title":"SceneScape: Text-Driven Consistent Scene Generation","date":"2023-02-02","arxiv_id":"2302.01133","repositories_listed":0,"syntology":null},{"url":null,"slug":"uncertainty-driven-dense-two-view-structure","title":"Uncertainty-Driven Dense Two-View Structure from Motion","date":"2023-02-01","arxiv_id":"2302.00523","repositories_listed":0,"syntology":null},{"url":null,"slug":"recurrent-structure-attention-guidance-for","title":"Recurrent Structure Attention Guidance for Depth Super-Resolution","date":"2023-01-31","arxiv_id":"2301.13419","repositories_listed":0,"syntology":null},{"url":null,"slug":"structure-flow-guided-network-for-real-depth","title":"Structure Flow-Guided Network for Real Depth Super-Resolution","date":"2023-01-31","arxiv_id":"2301.13416","repositories_listed":0,"syntology":null},{"url":null,"slug":"hdpv-slam-hybrid-depth-augmented-panoramic","title":"HDPV-SLAM: Hybrid Depth-augmented Panoramic Visual SLAM for Mobile Mapping System with Tilted LiDAR and Panoramic Visual Camera","date":"2023-01-27","arxiv_id":"2301.11823","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-the-third-dimension-in-contrastive","title":"Leveraging the Third Dimension in Contrastive Learning","date":"2023-01-27","arxiv_id":"2301.11790","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-good-features-to-transfer-across","title":"Learning Good Features to Transfer Across Tasks and Domains","date":"2023-01-26","arxiv_id":"2301.11310","repositories_listed":0,"syntology":null},{"url":null,"slug":"fg-depth-flow-guided-unsupervised-monocular","title":"FG-Depth: Flow-Guided Unsupervised Monocular Depth Estimation","date":"2023-01-20","arxiv_id":"2301.08414","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-light-field-depth-estimation-via","title":"Unsupervised Light Field Depth Estimation via Multi-view Feature Matching with Occlusion Prediction","date":"2023-01-20","arxiv_id":"2301.08433","repositories_listed":0,"syntology":null},{"url":null,"slug":"booster-a-benchmark-for-depth-from-images-of","title":"Booster: a Benchmark for Depth from Images of Specular and Transparent Surfaces","date":"2023-01-19","arxiv_id":"2301.08245","repositories_listed":0,"syntology":null},{"url":null,"slug":"softennet-symbiotic-monocular-depth","title":"SoftEnNet: Symbiotic Monocular Depth Estimation and Lumen Segmentation for Colonoscopy Endorobots","date":"2023-01-19","arxiv_id":"2301.08157","repositories_listed":0,"syntology":null},{"url":null,"slug":"dyna-depthformer-multi-frame-transformer-for","title":"Dyna-DepthFormer: Multi-frame Transformer for Self-Supervised Depth Estimation in Dynamic Scenes","date":"2023-01-14","arxiv_id":"2301.05871","repositories_listed":0,"syntology":null},{"url":null,"slug":"s-2-net-accurate-panorama-depth-estimation-on","title":"${S}^{2}$Net: Accurate Panorama Depth Estimation on Spherical Surface","date":"2023-01-14","arxiv_id":"2301.05845","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-planar-parallax-for-monocular-depth","title":"Deep Planar Parallax for Monocular Depth Estimation","date":"2023-01-09","arxiv_id":"2301.03178","repositories_listed":0,"syntology":null},{"url":null,"slug":"depthp-p-metric-accurate-monocular-depth","title":"DepthP+P: Metric Accurate Monocular Depth Estimation using Planar and Parallax","date":"2023-01-05","arxiv_id":"2301.02092","repositories_listed":0,"syntology":null},{"url":null,"slug":"bs3d-building-scale-3d-reconstruction-from","title":"BS3D: Building-scale 3D Reconstruction from RGB-D Images","date":"2023-01-03","arxiv_id":"2301.01057","repositories_listed":0,"syntology":null}],"record_sha256":"6310db52443aa422479980480a8073d39aa3e0fd668c17ed9225b8e0908ed5b7","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}