{"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/pose-estimation/papers/31","list_of":"/task/pose-estimation","task":"Pose 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":31,"pages_in_order":43,"rows_per_page":100,"rows":[3001,3100],"of":4228,"counts":{"archive_papers_tagged":4228,"with_a_code_link":1679,"where_syntology_ran_a_sample":376,"not_listed_spam_title":0,"listed":4228,"listed_where_code_ran":376,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":327,"every_run_a_failure_of_syntologys_instrument":49,"listed_with_a_run_with_no_instrument_failure":327,"listed_every_run_a_failure_of_syntologys_instrument":49,"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/pose-estimation","prev":"/task/pose-estimation/papers/30","next":"/task/pose-estimation/papers/32","papers":[{"url":null,"slug":"in-bed-human-pose-estimation-from-unseen-and","title":"In-Bed Human Pose Estimation from Unseen and Privacy-Preserving Image Domains","date":"2021-11-30","arxiv_id":"2111.15124","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-estimation-of-3d-human-shape","title":"Probabilistic Estimation of 3D Human Shape and Pose with a Semantic Local Parametric Model","date":"2021-11-30","arxiv_id":"2111.15404","repositories_listed":0,"syntology":null},{"url":null,"slug":"semi-supervised-3d-hand-shape-and-pose","title":"Semi-Supervised 3D Hand Shape and Pose Estimation with Label Propagation","date":"2021-11-30","arxiv_id":"2111.15199","repositories_listed":0,"syntology":null},{"url":"/paper/robin-a-benchmark-for-robustness-to","slug":"robin-a-benchmark-for-robustness-to","title":"OOD-CV: A Benchmark for Robustness to Out-of-Distribution Shifts of Individual Nuisances in Natural Images","date":"2021-11-29","arxiv_id":"2111.14341","repositories_listed":0,"syntology":null},{"url":null,"slug":"ai-supported-framework-of-semi-automatic","title":"AI-supported Framework of Semi-Automatic Monoplotting for Monocular Oblique Visual Data Analysis","date":"2021-11-28","arxiv_id":"2111.14021","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-pose-estimation-and-future-motion","title":"3D Pose Estimation and Future Motion Prediction from 2D Images","date":"2021-11-26","arxiv_id":"2111.13285","repositories_listed":0,"syntology":null},{"url":null,"slug":"surfemb-dense-and-continuous-correspondence","title":"SurfEmb: Dense and Continuous Correspondence Distributions for Object Pose Estimation with Learnt Surface Embeddings","date":"2021-11-26","arxiv_id":"2111.13489","repositories_listed":0,"syntology":null},{"url":null,"slug":"megloc-a-robust-and-accurate-visual","title":"MegLoc: A Robust and Accurate Visual Localization Pipeline","date":"2021-11-25","arxiv_id":"2111.13063","repositories_listed":0,"syntology":null},{"url":null,"slug":"quantised-transforming-auto-encoders","title":"Quantised Transforming Auto-Encoders: Achieving Equivariance to Arbitrary Transformations in Deep Networks","date":"2021-11-25","arxiv_id":"2111.12873","repositories_listed":0,"syntology":null},{"url":null,"slug":"sm3d-simultaneous-monocular-mapping-and-3d","title":"SM3D: Simultaneous Monocular Mapping and 3D Detection","date":"2021-11-24","arxiv_id":"2111.12643","repositories_listed":0,"syntology":null},{"url":"/paper/uda-cope-unsupervised-domain-adaptation-for","slug":"uda-cope-unsupervised-domain-adaptation-for","title":"UDA-COPE: Unsupervised Domain Adaptation for Category-level Object Pose Estimation","date":"2021-11-24","arxiv_id":"2111.12580","repositories_listed":0,"syntology":null},{"url":null,"slug":"lifting-2d-human-pose-to-3d-with-domain","title":"Lifting 2D Human Pose to 3D with Domain Adapted 3D Body Concept","date":"2021-11-23","arxiv_id":"2111.11969","repositories_listed":0,"syntology":null},{"url":null,"slug":"customizing-an-affective-tutoring-system","title":"Customizing an Affective Tutoring System Based on Facial Expression and Head Pose Estimation","date":"2021-11-21","arxiv_id":"2111.14262","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-deeper-look-into-deepcap","title":"A Deeper Look into DeepCap","date":"2021-11-20","arxiv_id":"2111.10563","repositories_listed":0,"syntology":null},{"url":null,"slug":"acr-pose-adversarial-canonical-representation","title":"ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation","date":"2021-11-20","arxiv_id":"2111.10524","repositories_listed":0,"syntology":null},{"url":null,"slug":"mpf6d-masked-pyramid-fusion-6d-pose","title":"MPF6D: Masked Pyramid Fusion 6D Pose Estimation","date":"2021-11-17","arxiv_id":"2111.09378","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-fitness-1","title":"Deep Learning for Fitness","date":"2021-11-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"pose-recognition-in-the-wild-animal-pose","title":"Pose Recognition in the Wild: Animal pose estimation using Agglomerative Clustering and Contrastive Learning","date":"2021-11-16","arxiv_id":"2111.08259","repositories_listed":0,"syntology":null},{"url":null,"slug":"uet-headpose-a-sensor-based-top-view-head","title":"UET-Headpose: A sensor-based top-view head pose dataset","date":"2021-11-13","arxiv_id":"2111.07039","repositories_listed":0,"syntology":null},{"url":null,"slug":"6d-pose-estimation-with-combined-deep","title":"6D Pose Estimation with Combined Deep Learning and 3D Vision Techniques for a Fast and Accurate Object Grasping","date":"2021-11-11","arxiv_id":"2111.06276","repositories_listed":0,"syntology":null},{"url":null,"slug":"dynamic-iterative-refinement-for-efficient-3d","title":"Dynamic Iterative Refinement for Efficient 3D Hand Pose Estimation","date":"2021-11-11","arxiv_id":"2111.06500","repositories_listed":0,"syntology":null},{"url":null,"slug":"monocular-human-shape-and-pose-with-dense","title":"Monocular Human Shape and Pose with Dense Mesh-borne Local Image Features","date":"2021-11-09","arxiv_id":"2111.05319","repositories_listed":0,"syntology":null},{"url":null,"slug":"rethinking-deconvolution-for-2d-human-pose","title":"Rethinking Deconvolution for 2D Human Pose Estimation Light yet Accurate Model for Real-time Edge Computing","date":"2021-11-08","arxiv_id":"2111.04226","repositories_listed":0,"syntology":null},{"url":null,"slug":"improving-pose-estimation-through-contextual","title":"Improving Pose Estimation through Contextual Activity Fusion","date":"2021-11-03","arxiv_id":"2111.02500","repositories_listed":0,"syntology":null},{"url":null,"slug":"higher-order-implicit-fairing-networks-for-3d","title":"Higher-Order Implicit Fairing Networks for 3D Human Pose Estimation","date":"2021-11-01","arxiv_id":"2111.00950","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-eye-in-hand-camera-calibration-from","title":"Learning Eye-in-Hand Camera Calibration from a Single Image","date":"2021-11-01","arxiv_id":"2111.01245","repositories_listed":0,"syntology":null},{"url":null,"slug":"leveraging-se-3-equivariance-for-self","title":"Leveraging SE(3) Equivariance for Self-Supervised Category-Level Object Pose Estimation","date":"2021-10-30","arxiv_id":"2111.00190","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-comparative-study-of-coarse-to-dense-3d","title":"A Comparative Study of Coarse to Dense 3D Indoor Scene Registration Algorithms","date":"2021-10-28","arxiv_id":"2110.15179","repositories_listed":0,"syntology":null},{"url":null,"slug":"incremental-learning-for-animal-pose","title":"Incremental Learning for Animal Pose Estimation using RBF k-DPP","date":"2021-10-26","arxiv_id":"2110.13598","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-dynamic-keypoints-selection-network-for","title":"A Dynamic Keypoints Selection Network for 6DoF Pose Estimation","date":"2021-10-24","arxiv_id":"2110.12401","repositories_listed":0,"syntology":null},{"url":null,"slug":"robust-edge-direct-visual-odometry-based-on","title":"Robust Edge-Direct Visual Odometry based on CNN edge detection and Shi-Tomasi corner optimization","date":"2021-10-21","arxiv_id":"2110.11064","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervision-and-spatial-sequential","title":"Self-Supervision and Spatial-Sequential Attention Based Loss for Multi-Person Pose Estimation","date":"2021-10-20","arxiv_id":"2110.10734","repositories_listed":0,"syntology":null},{"url":null,"slug":"accurate-and-robust-object-oriented-slam-with","title":"Accurate and Robust Object-oriented SLAM with 3D Quadric Landmark Construction in Outdoor Environment","date":"2021-10-18","arxiv_id":"2110.08977","repositories_listed":0,"syntology":null},{"url":null,"slug":"differentiable-rendering-with-perturbed","title":"Differentiable Rendering with Perturbed Optimizers","date":"2021-10-18","arxiv_id":"2110.09107","repositories_listed":0,"syntology":null},{"url":null,"slug":"do-you-see-what-i-see-using-augmented-reality","title":"Do You See What I See: Using Augmented Reality and Artificial Intelligence","date":"2021-10-16","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-human-pose-estimation-for-free-form","title":"3D Human Pose Estimation for Free-form Activity Using WiFi Signals","date":"2021-10-15","arxiv_id":"2110.08314","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-on-human-pose-estimation","title":"A Review on Human Pose Estimation","date":"2021-10-13","arxiv_id":"2110.06877","repositories_listed":0,"syntology":null},{"url":null,"slug":"event-based-high-speed-low-latency-fiducial","title":"Event-Based high-speed low-latency fiducial marker tracking","date":"2021-10-12","arxiv_id":"2110.05819","repositories_listed":0,"syntology":null},{"url":"/paper/adaptively-multi-view-and-temporal-fusing","slug":"adaptively-multi-view-and-temporal-fusing","title":"Adaptive Multi-view and Temporal Fusing Transformer for 3D Human Pose Estimation","date":"2021-10-11","arxiv_id":"2110.05092","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-low-cost-multi-person-3d-pose","title":"Real-time, low-cost multi-person 3D pose estimation","date":"2021-10-11","arxiv_id":"2110.11414","repositories_listed":0,"syntology":null},{"url":null,"slug":"6d-vit-category-level-6d-object-pose","title":"6D-ViT: Category-Level 6D Object Pose Estimation via Transformer-based Instance Representation Learning","date":"2021-10-10","arxiv_id":"2110.04792","repositories_listed":0,"syntology":null},{"url":null,"slug":"unsupervised-pose-aware-part-decomposition-1","title":"Unsupervised Pose-Aware Part Decomposition for 3D Articulated Objects","date":"2021-10-08","arxiv_id":"2110.04411","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-baseline-framework-for-part-level-action","title":"A Baseline Framework for Part-level Action Parsing and Action Recognition","date":"2021-10-07","arxiv_id":"2110.03368","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-autoencoder-self-supervised-1","title":"Video Autoencoder: self-supervised disentanglement of static 3D structure and motion","date":"2021-10-06","arxiv_id":"2110.02951","repositories_listed":0,"syntology":null},{"url":null,"slug":"vision-based-excavator-activity-analysis-and","title":"Construction Site Safety Monitoring and Excavator Activity Analysis System","date":"2021-10-06","arxiv_id":"2110.03083","repositories_listed":0,"syntology":null},{"url":"/paper/shape-aware-multi-person-pose-estimation-from-1","slug":"shape-aware-multi-person-pose-estimation-from-1","title":"Shape-aware Multi-Person Pose Estimation from Multi-View Images","date":"2021-10-05","arxiv_id":"2110.02330","repositories_listed":0,"syntology":null},{"url":null,"slug":"precise-object-placement-with-pose-distance","title":"Precise Object Placement with Pose Distance Estimations for Different Objects and Grippers","date":"2021-10-03","arxiv_id":"2110.00992","repositories_listed":0,"syntology":null},{"url":null,"slug":"monocinis-camera-independent-monocular-3d","title":"MonoCInIS: Camera Independent Monocular 3D Object Detection using Instance Segmentation","date":"2021-10-01","arxiv_id":"2110.00464","repositories_listed":0,"syntology":null},{"url":"/paper/stochastic-modeling-for-learnable-human-pose","slug":"stochastic-modeling-for-learnable-human-pose","title":"Generalizable Human Pose Triangulation","date":"2021-10-01","arxiv_id":"2110.00280","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-tactile-grasp-force-sensing-using","title":"Real-Time Tactile Grasp Force Sensing Using Fingernail Imaging via Deep Neural Networks","date":"2021-09-30","arxiv_id":"2109.15231","repositories_listed":0,"syntology":null},{"url":null,"slug":"bayesian-imbalanced-regression-debiasing","title":"Bayesian Imbalanced Regression Debiasing","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"dive-deeper-into-integral-pose-regression","title":"Dive Deeper Into Integral Pose Regression","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-learning-of-motion-informed","title":"Self-Supervised Learning of Motion-Informed Latents","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"spatiotemporal-characterization-of-gait-from","title":"Spatiotemporal Characterization of Gait from Monocular Videos with Transformers","date":"2021-09-29","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"understanding-egocentric-hand-object","title":"Understanding Egocentric Hand-Object Interactions from Hand Pose Estimation","date":"2021-09-29","arxiv_id":"2109.14657","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-hand-pose-and-shape-estimation-from-rgb","title":"3D Hand Pose and Shape Estimation from RGB Images for Keypoint-Based Hand Gesture Recognition","date":"2021-09-28","arxiv_id":"2109.13879","repositories_listed":0,"syntology":null},{"url":null,"slug":"fully-differentiable-and-interpretable-model","title":"Learning Interpretable BEV Based VIO without Deep Neural Networks","date":"2021-09-25","arxiv_id":"2109.12292","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-stereopsis-from-geometric-synthesis","title":"Learning Stereopsis from Geometric Synthesis for 6D Object Pose Estimation","date":"2021-09-25","arxiv_id":"2109.12266","repositories_listed":0,"syntology":null},{"url":null,"slug":"pranet-point-cloud-registration-with-an","title":"PRANet: Point Cloud Registration with an Artificial Agent","date":"2021-09-23","arxiv_id":"2109.11349","repositories_listed":0,"syntology":null},{"url":null,"slug":"t6d-direct-transformers-for-multi-object-6d","title":"T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression","date":"2021-09-22","arxiv_id":"2109.10948","repositories_listed":0,"syntology":null},{"url":null,"slug":"kdfnet-learning-keypoint-distance-field-for","title":"KDFNet: Learning Keypoint Distance Field for 6D Object Pose Estimation","date":"2021-09-21","arxiv_id":"2109.10127","repositories_listed":0,"syntology":null},{"url":null,"slug":"physics-based-human-motion-estimation-and","title":"Physics-based Human Motion Estimation and Synthesis from Videos","date":"2021-09-21","arxiv_id":"2109.09913","repositories_listed":0,"syntology":null},{"url":null,"slug":"single-person-pose-estimation-a-survey","title":"Single Person Pose Estimation: A Survey","date":"2021-09-21","arxiv_id":"2109.10056","repositories_listed":0,"syntology":null},{"url":null,"slug":"stereobj-1m-large-scale-stereo-image-dataset","title":"StereOBJ-1M: Large-scale Stereo Image Dataset for 6D Object Pose Estimation","date":"2021-09-21","arxiv_id":"2109.10115","repositories_listed":0,"syntology":null},{"url":null,"slug":"low-resolution-human-pose-estimation","title":"Low-resolution Human Pose Estimation","date":"2021-09-19","arxiv_id":"2109.09090","repositories_listed":0,"syntology":null},{"url":null,"slug":"neural-network-based-lidar-gesture","title":"Neural Network Based Lidar Gesture Recognition for Realtime Robot Teleoperation","date":"2021-09-17","arxiv_id":"2109.08263","repositories_listed":0,"syntology":null},{"url":null,"slug":"hybrid-icp","title":"Hybrid ICP","date":"2021-09-15","arxiv_id":"2109.07559","repositories_listed":0,"syntology":null},{"url":"/paper/learning-dynamical-human-joint-affinity-for","slug":"learning-dynamical-human-joint-affinity-for","title":"Learning Dynamical Human-Joint Affinity for 3D Pose Estimation in Videos","date":"2021-09-15","arxiv_id":"2109.07353","repositories_listed":0,"syntology":null},{"url":null,"slug":"s3lam-structured-scene-slam","title":"S3LAM: Structured Scene SLAM","date":"2021-09-15","arxiv_id":"2109.07339","repositories_listed":0,"syntology":null},{"url":null,"slug":"deep-learning-for-fitness","title":"Deep Learning for Fitness","date":"2021-09-03","arxiv_id":"2109.01376","repositories_listed":0,"syntology":null},{"url":null,"slug":"category-level-metric-scale-object-shape-and","title":"Category-Level Metric Scale Object Shape and Pose Estimation","date":"2021-09-01","arxiv_id":"2109.00326","repositories_listed":0,"syntology":null},{"url":null,"slug":"eventpoint-self-supervised-local-descriptor","title":"EventPoint: Self-Supervised Interest Point Detection and Description for Event-based Camera","date":"2021-09-01","arxiv_id":"2109.00210","repositories_listed":0,"syntology":null},{"url":null,"slug":"deepfake-detection-with-inconsistent-head","title":"DeepFake Detection with Inconsistent Head Poses: Reproducibility and Analysis","date":"2021-08-28","arxiv_id":"2108.12715","repositories_listed":0,"syntology":null},{"url":null,"slug":"goal-driven-text-descriptions-for-images","title":"Goal-driven text descriptions for images","date":"2021-08-28","arxiv_id":"2108.12575","repositories_listed":0,"syntology":null},{"url":"/paper/arshoe-real-time-augmented-reality-shoe-try","slug":"arshoe-real-time-augmented-reality-shoe-try","title":"ARShoe: Real-Time Augmented Reality Shoe Try-on System on Smartphones","date":"2021-08-24","arxiv_id":"2108.10515","repositories_listed":0,"syntology":null},{"url":null,"slug":"chinet-deep-recurrent-convolutional-learning","title":"ChiNet: Deep Recurrent Convolutional Learning for Multimodal Spacecraft Pose Estimation","date":"2021-08-23","arxiv_id":"2108.10282","repositories_listed":0,"syntology":null},{"url":null,"slug":"pr-gcn-a-deep-graph-convolutional-network","title":"PR-GCN: A Deep Graph Convolutional Network with Point Refinement for 6D Pose Estimation","date":"2021-08-23","arxiv_id":"2108.09916","repositories_listed":0,"syntology":null},{"url":null,"slug":"knowledge-distillation-from-ensemble-of","title":"Boosting of Head Pose Estimation by Knowledge Distillation","date":"2021-08-20","arxiv_id":"2108.09183","repositories_listed":0,"syntology":null},{"url":null,"slug":"category-level-6d-object-pose-estimation-via","title":"Category-Level 6D Object Pose Estimation via Cascaded Relation and Recurrent Reconstruction Networks","date":"2021-08-19","arxiv_id":"2108.08755","repositories_listed":0,"syntology":null},{"url":"/paper/learning-skeletal-graph-neural-networks-for","slug":"learning-skeletal-graph-neural-networks-for","title":"Learning Skeletal Graph Neural Networks for Hard 3D Pose Estimation","date":"2021-08-16","arxiv_id":"2108.07181","repositories_listed":0,"syntology":null},{"url":null,"slug":"reassessing-the-limitations-of-cnn-methods","title":"Reassessing the Limitations of CNN Methods for Camera Pose Regression","date":"2021-08-16","arxiv_id":"2108.07260","repositories_listed":0,"syntology":null},{"url":null,"slug":"multitask-centernet-mcn-efficient-and-diverse","title":"MultiTask-CenterNet (MCN): Efficient and Diverse Multitask Learning using an Anchor Free Approach","date":"2021-08-11","arxiv_id":"2108.05060","repositories_listed":0,"syntology":null},{"url":null,"slug":"how-self-supervised-learning-can-be-used-for","title":"How Self-Supervised Learning Can be Used for Fine-Grained Head Pose Estimation?","date":"2021-08-10","arxiv_id":"2108.04893","repositories_listed":0,"syntology":null},{"url":null,"slug":"self-supervised-learning-of-occlusion-aware","title":"Self-supervised Learning of Occlusion Aware Flow Guided 3D Geometry Perception with Adaptive Cross Weighted Loss from Monocular Videos","date":"2021-08-09","arxiv_id":"2108.03893","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-volumetric-change-detection-framework-using","title":"A volumetric change detection framework using UAV oblique photogrammetry - A case study of ultra-high-resolution monitoring of progressive building collapse","date":"2021-08-05","arxiv_id":"2108.02800","repositories_listed":0,"syntology":null},{"url":null,"slug":"simultaneous-semantic-and-collision-learning","title":"Simultaneous Semantic and Collision Learning for 6-DoF Grasp Pose Estimation","date":"2021-08-05","arxiv_id":"2108.02425","repositories_listed":0,"syntology":null},{"url":"/paper/voxeltrack-multi-person-3d-human-pose","slug":"voxeltrack-multi-person-3d-human-pose","title":"VoxelTrack: Multi-Person 3D Human Pose Estimation and Tracking in the Wild","date":"2021-08-05","arxiv_id":"2108.02452","repositories_listed":0,"syntology":null},{"url":null,"slug":"active-perception-for-ambiguous-objects","title":"Active Perception for Ambiguous Objects Classification","date":"2021-08-02","arxiv_id":"2108.00737","repositories_listed":0,"syntology":null},{"url":null,"slug":"posefusion2-simultaneous-background","title":"PoseFusion2: Simultaneous Background Reconstruction and Human Shape Recovery in Real-time","date":"2021-08-02","arxiv_id":"2108.00695","repositories_listed":0,"syntology":null},{"url":"/paper/sydog-a-synthetic-dog-dataset-for-improved-2d","slug":"sydog-a-synthetic-dog-dataset-for-improved-2d","title":"SyDog: A Synthetic Dog Dataset for Improved 2D Pose Estimation","date":"2021-07-31","arxiv_id":"2108.00249","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-human-pose-estimation-by-maximizing","title":"Efficient Human Pose Estimation by Maximizing Fusion and High-Level Spatial Attention","date":"2021-07-29","arxiv_id":"2107.13693","repositories_listed":0,"syntology":null},{"url":null,"slug":"viewpoint-invariant-exercise-repetition","title":"Viewpoint-Invariant Exercise Repetition Counting","date":"2021-07-29","arxiv_id":"2107.13760","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-based-depth-and-pose-estimation-for","title":"Learning-Based Depth and Pose Estimation for Monocular Endoscope with Loss Generalization","date":"2021-07-28","arxiv_id":"2107.13263","repositories_listed":0,"syntology":null},{"url":null,"slug":"lighter-stacked-hourglass-human-pose","title":"Lighter Stacked Hourglass Human Pose Estimation","date":"2021-07-28","arxiv_id":"2107.13643","repositories_listed":0,"syntology":null},{"url":null,"slug":"sign-and-search-sign-search-functionality-for","title":"Sign and Search: Sign Search Functionality for Sign Language Lexica","date":"2021-07-28","arxiv_id":"2107.13637","repositories_listed":0,"syntology":null},{"url":null,"slug":"real-time-keypoints-detection-for-autonomous","title":"Real-time Keypoints Detection for Autonomous Recovery of the Unmanned Ground Vehicle","date":"2021-07-27","arxiv_id":"2107.12852","repositories_listed":0,"syntology":null},{"url":null,"slug":"vipose-real-time-visual-inertial-6d-object","title":"VIPose: Real-time Visual-Inertial 6D Object Pose Tracking","date":"2021-07-27","arxiv_id":"2107.12617","repositories_listed":0,"syntology":null},{"url":"/paper/monoindoor-towards-good-practice-of-self","slug":"monoindoor-towards-good-practice-of-self","title":"MonoIndoor: Towards Good Practice of Self-Supervised Monocular Depth Estimation for Indoor Environments","date":"2021-07-26","arxiv_id":"2107.12429","repositories_listed":0,"syntology":null},{"url":null,"slug":"bangla-sign-language-recognition-using","title":"Bangla sign language recognition using concatenated BdSL network","date":"2021-07-25","arxiv_id":"2107.11818","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-large-scale-inlier-voting-for","title":"Efficient Large Scale Inlier Voting for Geometric Vision Problems","date":"2021-07-25","arxiv_id":"2107.11810","repositories_listed":0,"syntology":null}],"record_sha256":"e9efaa5c982b642d42e025a31ce326d48de6fb45dbaa9bf92a570227f6003abb","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}