{"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/object/papers/90","list_of":"/task/object","task":"Object","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":90,"pages_in_order":107,"rows_per_page":100,"rows":[8901,9000],"of":10696,"counts":{"archive_papers_tagged":10696,"with_a_code_link":3979,"where_syntology_ran_a_sample":1043,"not_listed_spam_title":0,"listed":10696,"listed_where_code_ran":1043,"where_syntology_ran_a_sample_split":{"with_a_run_with_no_instrument_failure":919,"every_run_a_failure_of_syntologys_instrument":124,"listed_with_a_run_with_no_instrument_failure":919,"listed_every_run_a_failure_of_syntologys_instrument":124,"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/object","prev":"/task/object/papers/89","next":"/task/object/papers/91","papers":[{"url":null,"slug":"multi-task-self-supervised-object-detection","title":"Multi-Task Self-Supervised Object Detection via Recycling of Bounding Box Annotations","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"object-detection-with-location-aware","title":"Object Detection With Location-Aware Deformable Convolution and Backward Attention Filtering","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"salient-object-detection-with-pyramid","title":"Salient Object Detection With Pyramid Attention and Salient Edges","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-aware-graph-relation-network-for","title":"Spatial-Aware Graph Relation Network for Large-Scale Object Detection","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/you-reap-what-you-sow-using-videos-to","slug":"you-reap-what-you-sow-using-videos-to","title":"You Reap What You Sow: Using Videos to Generate High Precision Object Proposals for Weakly-Supervised Object Detection","date":"2019-06-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"190600093","title":"Driver Behavior Analysis Using Lane Departure Detection Under Challenging Conditions","date":"2019-05-31","arxiv_id":"1906.00093","repositories_listed":0,"syntology":null},{"url":null,"slug":"190600786","title":"Efficient Object Detection Model for Real-Time UAV Applications","date":"2019-05-30","arxiv_id":"1906.00786","repositories_listed":0,"syntology":null},{"url":null,"slug":"applying-generative-adversarial-networks-to","title":"Applying Generative Adversarial Networks to Intelligent Subsurface Imaging and Identification","date":"2019-05-30","arxiv_id":"1905.13321","repositories_listed":0,"syntology":null},{"url":null,"slug":"grounding-language-attributes-to-objects","title":"Grounding Language Attributes to Objects using Bayesian Eigenobjects","date":"2019-05-30","arxiv_id":"1905.13153","repositories_listed":0,"syntology":null},{"url":null,"slug":"hierarchical-structure-and-joint-training-for","title":"CS-R-FCN: Cross-supervised Learning for Large-Scale Object Detection","date":"2019-05-30","arxiv_id":"1905.12863","repositories_listed":0,"syntology":null},{"url":"/paper/disentangling-monocular-3d-object-detection","slug":"disentangling-monocular-3d-object-detection","title":"Disentangling Monocular 3D Object Detection","date":"2019-05-29","arxiv_id":"1905.12365","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-analysis-of-object-embeddings-for-image","title":"Efficient Object Embedding for Spliced Image Retrieval","date":"2019-05-28","arxiv_id":"1905.11903","repositories_listed":0,"syntology":null},{"url":null,"slug":"compositional-convolutional-networks-for","title":"Combining Compositional Models and Deep Networks For Robust Object Classification under Occlusion","date":"2019-05-28","arxiv_id":"1905.11826","repositories_listed":0,"syntology":null},{"url":null,"slug":"probabilistic-category-level-pose-estimation","title":"Probabilistic Category-Level Pose Estimation via Segmentation and Predicted-Shape Priors","date":"2019-05-28","arxiv_id":"1905.12079","repositories_listed":0,"syntology":null},{"url":null,"slug":"union-visual-translation-embedding-for-visual","title":"Contextual Translation Embedding for Visual Relationship Detection and Scene Graph Generation","date":"2019-05-28","arxiv_id":"1905.11624","repositories_listed":0,"syntology":null},{"url":null,"slug":"190511522","title":"Enhancing Salient Object Segmentation Through Attention","date":"2019-05-27","arxiv_id":"1905.11522","repositories_listed":0,"syntology":null},{"url":null,"slug":"fourier-based-rotation-invariant-feature","title":"Fourier-based Rotation-invariant Feature Boosting: An Efficient Framework for Geospatial Object Detection","date":"2019-05-27","arxiv_id":"1905.11074","repositories_listed":0,"syntology":null},{"url":null,"slug":"semantic-fisher-scores-for-task-transfer","title":"Semantic Fisher Scores for Task Transfer: Using Objects to Classify Scenes","date":"2019-05-27","arxiv_id":"1905.11539","repositories_listed":0,"syntology":null},{"url":null,"slug":"enhancing-ml-robustness-using-physical-world","title":"Rearchitecting Classification Frameworks For Increased Robustness","date":"2019-05-26","arxiv_id":"1905.10900","repositories_listed":0,"syntology":null},{"url":null,"slug":"efficient-object-annotation-via-speaking-and","title":"Efficient Object Annotation via Speaking and Pointing","date":"2019-05-25","arxiv_id":"1905.10576","repositories_listed":0,"syntology":null},{"url":null,"slug":"ovsnet-towards-one-pass-real-time-video","title":"OVSNet : Towards One-Pass Real-Time Video Object Segmentation","date":"2019-05-24","arxiv_id":"1905.10064","repositories_listed":0,"syntology":null},{"url":null,"slug":"shift-r-cnn-deep-monocular-3d-object","title":"Shift R-CNN: Deep Monocular 3D Object Detection with Closed-Form Geometric Constraints","date":"2019-05-23","arxiv_id":"1905.09970","repositories_listed":0,"syntology":null},{"url":null,"slug":"through-wall-object-recognition-and-pose","title":"Through-Wall Object Recognition and Pose Estimation","date":"2019-05-21","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"enabling-computer-vision-driven-assistive","title":"Enabling Computer Vision Driven Assistive Devices for the Visually Impaired via Micro-architecture Design Exploration","date":"2019-05-20","arxiv_id":"1905.07836","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-count-objects-with-few-exemplar","title":"Learning to Count Objects with Few Exemplar Annotations","date":"2019-05-20","arxiv_id":"1905.07898","repositories_listed":0,"syntology":null},{"url":null,"slug":"u-net-based-multi-instance-video-object","title":"U-Net Based Multi-instance Video Object Segmentation","date":"2019-05-19","arxiv_id":"1905.07826","repositories_listed":0,"syntology":null},{"url":null,"slug":"training-object-detectors-with-noisy-data","title":"Training Object Detectors With Noisy Data","date":"2019-05-17","arxiv_id":"1905.07202","repositories_listed":0,"syntology":null},{"url":null,"slug":"tracking-in-urban-traffic-scenes-from","title":"Tracking in Urban Traffic Scenes from Background Subtraction and Object Detection","date":"2019-05-15","arxiv_id":"1905.06381","repositories_listed":0,"syntology":null},{"url":null,"slug":"monocular-3d-object-detection-via-geometric","title":"Monocular 3D Object Detection via Geometric Reasoning on Keypoints","date":"2019-05-14","arxiv_id":"1905.05618","repositories_listed":0,"syntology":null},{"url":null,"slug":"190508843","title":"Joint Object and State Recognition using Language Knowledge","date":"2019-05-13","arxiv_id":"1905.08843","repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-search-efficiently-using","title":"Scalable and Efficient Comparison-based Search without Features","date":"2019-05-13","arxiv_id":"1905.05049","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-detection-in-specific-traffic-scenes","title":"Object Detection in Specific Traffic Scenes using YOLOv2","date":"2019-05-12","arxiv_id":"1905.04740","repositories_listed":0,"syntology":null},{"url":null,"slug":"unified-generator-classifier-for-efficient","title":"Unified Generator-Classifier for Efficient Zero-Shot Learning","date":"2019-05-11","arxiv_id":"1905.04511","repositories_listed":0,"syntology":null},{"url":null,"slug":"building-3d-object-models-during-manipulation","title":"Building 3D Object Models during Manipulation by Reconstruction-Aware Trajectory Optimization","date":"2019-05-10","arxiv_id":"1905.03907","repositories_listed":0,"syntology":null},{"url":null,"slug":"support-relation-analysis-for-objects-in","title":"Support Relation Analysis for Objects in Multiple View RGB-D Images","date":"2019-05-10","arxiv_id":"1905.04084","repositories_listed":0,"syntology":null},{"url":null,"slug":"190503434","title":"ROSA: Robust Salient Object Detection against Adversarial Attacks","date":"2019-05-09","arxiv_id":"1905.03434","repositories_listed":0,"syntology":null},{"url":null,"slug":"goal-oriented-object-importance-estimation-in","title":"Goal-oriented Object Importance Estimation in On-road Driving Videos","date":"2019-05-08","arxiv_id":"1905.02848","repositories_listed":0,"syntology":null},{"url":null,"slug":"number-detectors-spontaneously-emerge-in-a","title":"Number detectors spontaneously emerge in a deep neural network designed for visual object recognition","date":"2019-05-08","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"training-a-fast-object-detector-for-lidar","title":"Training a Fast Object Detector for LiDAR Range Images Using Labeled Data from Sensors with Higher Resolution","date":"2019-05-08","arxiv_id":"1905.03066","repositories_listed":0,"syntology":null},{"url":null,"slug":"190503697","title":"On Applying Machine Learning/Object Detection Models for Analysing Digitally Captured Physical Prototypes from Engineering Design Projects","date":"2019-05-07","arxiv_id":"1905.03697","repositories_listed":0,"syntology":null},{"url":null,"slug":"object-exchangeability-in-reinforcement","title":"Object Exchangeability in Reinforcement Learning: Extended Abstract","date":"2019-05-07","arxiv_id":"1905.02698","repositories_listed":0,"syntology":null},{"url":null,"slug":"creating-lightweight-object-detectors-with","title":"Creating Lightweight Object Detectors with Model Compression for Deployment on Edge Devices","date":"2019-05-06","arxiv_id":"1905.01787","repositories_listed":0,"syntology":null},{"url":null,"slug":"frame-wise-motion-and-appearance-for-real","title":"Frame-wise Motion and Appearance for Real-time Multiple Object Tracking","date":"2019-05-06","arxiv_id":"1905.02292","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-review-of-object-detection-models-based-on","title":"A Review of Object Detection Models based on Convolutional Neural Network","date":"2019-05-05","arxiv_id":"1905.01614","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-exploring-undetermined-relationships-for","title":"On Exploring Undetermined Relationships for Visual Relationship Detection","date":"2019-05-05","arxiv_id":"1905.01595","repositories_listed":0,"syntology":null},{"url":null,"slug":"190503707","title":"Human Activity Recognition Using Visual Object Detection","date":"2019-05-02","arxiv_id":"1905.03707","repositories_listed":0,"syntology":null},{"url":null,"slug":"egocentric-hand-track-and-object-based-human","title":"Egocentric Hand Track and Object-based Human Action Recognition","date":"2019-05-02","arxiv_id":"1905.00742","repositories_listed":0,"syntology":null},{"url":null,"slug":"the-2019-davis-challenge-on-vos-unsupervised","title":"The 2019 DAVIS Challenge on VOS: Unsupervised Multi-Object Segmentation","date":"2019-05-02","arxiv_id":"1905.00737","repositories_listed":0,"syntology":null},{"url":null,"slug":"classification-in-the-dark-using-tactile","title":"Classification in the dark using tactile exploration","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"distributional-interaction-of-concreteness","title":"Distributional Interaction of Concreteness and Abstractness in Verb--Noun Subcategorisation","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-object-localization-via-sensitivity","title":"FAST OBJECT LOCALIZATION VIA SENSITIVITY ANALYSIS","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"learning-to-refer-to-3d-objects-with-natural","title":"Learning to Refer to 3D Objects with Natural Language","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"modeling-parts-structure-and-system-dynamics","title":"Modeling Parts, Structure, and System Dynamics via Predictive Learning","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"object-oriented-model-learning-through-multi","title":"Object-Oriented Model Learning through Multi-Level Abstraction","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":null,"slug":"reasoning-about-physical-interactions-with","title":"Reasoning About Physical Interactions with Object-Centric Models","date":"2019-05-01","arxiv_id":null,"repositories_listed":0,"syntology":null},{"url":"/paper/segmentation-is-all-you-need","slug":"segmentation-is-all-you-need","title":"Segmentation is All You Need","date":"2019-04-30","arxiv_id":"1904.13300","repositories_listed":0,"syntology":null},{"url":null,"slug":"wearable-travel-aid-for-environment","title":"Wearable Travel Aid for Environment Perception and Navigation of Visually Impaired People","date":"2019-04-30","arxiv_id":"1904.13037","repositories_listed":0,"syntology":null},{"url":null,"slug":"190412483","title":"Self-Attention Capsule Networks for Object Classification","date":"2019-04-29","arxiv_id":"1904.12483","repositories_listed":0,"syntology":null},{"url":null,"slug":"deephmap-combined-projection-grouping-and","title":"DeepHMap++: Combined Projection Grouping and Correspondence Learning for Full DoF Pose Estimation","date":"2019-04-29","arxiv_id":"1904.12735","repositories_listed":0,"syntology":null},{"url":null,"slug":"mixture-of-pre-processing-experts-model-for-1","title":"Mixture of Pre-processing Experts Model for Noise Robust Deep Learning on Resource Constrained Platforms","date":"2019-04-29","arxiv_id":"1904.12426","repositories_listed":0,"syntology":null},{"url":null,"slug":"3d-sic-3d-semantic-instance-completion-for","title":"RevealNet: Seeing Behind Objects in RGB-D Scans","date":"2019-04-26","arxiv_id":"1904.12012","repositories_listed":0,"syntology":null},{"url":null,"slug":"a-large-scale-urban-surveillance-video","title":"A Large Scale Urban Surveillance Video Dataset for Multiple-Object Tracking and Behavior Analysis","date":"2019-04-26","arxiv_id":"1904.11784","repositories_listed":0,"syntology":null},{"url":"/paper/deep-fitting-degree-scoring-network-for","slug":"deep-fitting-degree-scoring-network-for","title":"Deep Fitting Degree Scoring Network for Monocular 3D Object Detection","date":"2019-04-26","arxiv_id":"1904.12681","repositories_listed":0,"syntology":null},{"url":null,"slug":"har-net-joint-learning-of-hybrid-attention","title":"HAR-Net: Joint Learning of Hybrid Attention for Single-stage Object Detection","date":"2019-04-25","arxiv_id":"1904.11141","repositories_listed":0,"syntology":null},{"url":null,"slug":"on-guiding-video-object-segmentation","title":"On guiding video object segmentation","date":"2019-04-25","arxiv_id":"1904.11256","repositories_listed":0,"syntology":null},{"url":null,"slug":"pointing-novel-objects-in-image-captioning","title":"Pointing Novel Objects in Image Captioning","date":"2019-04-25","arxiv_id":"1904.11251","repositories_listed":0,"syntology":null},{"url":null,"slug":"sensor-fusion-for-joint-3d-object-detection","title":"Sensor Fusion for Joint 3D Object Detection and Semantic Segmentation","date":"2019-04-25","arxiv_id":"1904.11466","repositories_listed":0,"syntology":null},{"url":null,"slug":"spatial-temporal-relation-networks-for-multi","title":"Spatial-Temporal Relation Networks for Multi-Object Tracking","date":"2019-04-25","arxiv_id":"1904.11489","repositories_listed":0,"syntology":null},{"url":null,"slug":"190412638","title":"Context-Aware Zero-Shot Learning for Object Recognition","date":"2019-04-24","arxiv_id":"1904.12638","repositories_listed":0,"syntology":null},{"url":null,"slug":"190412665","title":"PCA-RECT: An Energy-efficient Object Detection Approach for Event Cameras","date":"2019-04-24","arxiv_id":"1904.12665","repositories_listed":0,"syntology":null},{"url":null,"slug":"physical-adversarial-textures-that-fool","title":"Physical Adversarial Textures that Fool Visual Object Tracking","date":"2019-04-24","arxiv_id":"1904.11042","repositories_listed":0,"syntology":null},{"url":null,"slug":"tactile-mapping-and-localization-from-high","title":"Tactile Mapping and Localization from High-Resolution Tactile Imprints","date":"2019-04-24","arxiv_id":"1904.10944","repositories_listed":0,"syntology":null},{"url":null,"slug":"drishtikon-an-advanced-navigational-aid","title":"Drishtikon: An advanced navigational aid system for visually impaired people","date":"2019-04-23","arxiv_id":"1904.10351","repositories_listed":0,"syntology":null},{"url":null,"slug":"transferable-semi-supervised-3d-object","title":"Transferable Semi-supervised 3D Object Detection from RGB-D Data","date":"2019-04-23","arxiv_id":"1904.10300","repositories_listed":0,"syntology":null},{"url":null,"slug":"190412618","title":"Deep Learning Based Automatic Video Annotation Tool for Self-Driving Car","date":"2019-04-19","arxiv_id":"1904.12618","repositories_listed":0,"syntology":null},{"url":null,"slug":"190412619","title":"Multiple receptive fields and small-object-focusing weakly-supervised segmentation network for fast object detection","date":"2019-04-19","arxiv_id":"1904.12619","repositories_listed":0,"syntology":null},{"url":null,"slug":"automated-focal-loss-for-image-based-object","title":"Automated Focal Loss for Image based Object Detection","date":"2019-04-19","arxiv_id":"1904.09048","repositories_listed":0,"syntology":null},{"url":null,"slug":"video-object-segmentation-and-tracking-a","title":"Video Object Segmentation and Tracking: A Survey","date":"2019-04-19","arxiv_id":"1904.09172","repositories_listed":0,"syntology":null},{"url":"/paper/deep-optics-for-monocular-depth-estimation","slug":"deep-optics-for-monocular-depth-estimation","title":"Deep Optics for Monocular Depth Estimation and 3D Object Detection","date":"2019-04-18","arxiv_id":"1904.08601","repositories_listed":0,"syntology":null},{"url":null,"slug":"discriminative-online-learning-for-fast-video","title":"Discriminative Online Learning for Fast Video Object Segmentation","date":"2019-04-18","arxiv_id":"1904.08630","repositories_listed":0,"syntology":null},{"url":null,"slug":"repgnobject-detection-with-relational","title":"RepGN:Object Detection with Relational Proposal Graph Network","date":"2019-04-18","arxiv_id":"1904.08959","repositories_listed":0,"syntology":null},{"url":null,"slug":"salient-object-detection-a-distinctive","title":"Salient Object Detection: A Distinctive Feature Integration Model","date":"2019-04-18","arxiv_id":"1904.08868","repositories_listed":0,"syntology":null},{"url":null,"slug":"2d-car-detection-in-radar-data-with-pointnets","title":"2D Car Detection in Radar Data with PointNets","date":"2019-04-17","arxiv_id":"1904.08414","repositories_listed":0,"syntology":null},{"url":null,"slug":"algorithm-for-the-reconstruction-of-dynamic","title":"Algorithm for the reconstruction of dynamic objects in CT-scanning using optical flow","date":"2019-04-17","arxiv_id":"1905.00723","repositories_listed":0,"syntology":null},{"url":null,"slug":"graph-based-dynamic-segmentation-of-generic","title":"Graph based Dynamic Segmentation of Generic Objects in 3D","date":"2019-04-17","arxiv_id":"1904.08518","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-extended-description-logic-system-with","title":"An extended description logic system with knowledge element based on ALC","date":"2019-04-16","arxiv_id":"1904.07469","repositories_listed":0,"syntology":null},{"url":null,"slug":"complexer-yolo-real-time-3d-object-detection","title":"Complexer-YOLO: Real-Time 3D Object Detection and Tracking on Semantic Point Clouds","date":"2019-04-16","arxiv_id":"1904.07537","repositories_listed":0,"syntology":null},{"url":null,"slug":"fast-inference-in-capsule-networks-using","title":"Fast Inference in Capsule Networks Using Accumulated Routing Coefficients","date":"2019-04-15","arxiv_id":"1904.07304","repositories_listed":0,"syntology":null},{"url":null,"slug":"simco-similarity-based-object-counting","title":"SIMCO: SIMilarity-based object COunting","date":"2019-04-15","arxiv_id":"1904.07092","repositories_listed":0,"syntology":null},{"url":null,"slug":"universal-bounding-box-regression-and-its","title":"Universal Bounding Box Regression and Its Applications","date":"2019-04-15","arxiv_id":"1904.06805","repositories_listed":0,"syntology":null},{"url":null,"slug":"190406726","title":"VORNet: Spatio-temporally Consistent Video Inpainting for Object Removal","date":"2019-04-14","arxiv_id":"1904.06726","repositories_listed":0,"syntology":null},{"url":null,"slug":"speechyolo-detection-and-localization-of","title":"SpeechYOLO: Detection and Localization of Speech Objects","date":"2019-04-14","arxiv_id":"1904.07704","repositories_listed":0,"syntology":null},{"url":null,"slug":"combining-physical-simulators-and-object","title":"Combining Physical Simulators and Object-Based Networks for Control","date":"2019-04-13","arxiv_id":"1904.06580","repositories_listed":0,"syntology":null},{"url":null,"slug":"an-analysis-of-pre-training-on-object","title":"An Analysis of Pre-Training on Object Detection","date":"2019-04-11","arxiv_id":"1904.05871","repositories_listed":0,"syntology":null},{"url":null,"slug":"detecting-repeating-objects-using-patch-1","title":"Detecting Repeating Objects using Patch Correlation Analysis","date":"2019-04-11","arxiv_id":"1904.05629","repositories_listed":0,"syntology":null},{"url":null,"slug":"baod-budget-aware-object-detection","title":"BAOD: Budget-Aware Object Detection","date":"2019-04-10","arxiv_id":"1904.05443","repositories_listed":0,"syntology":null},{"url":null,"slug":"evaluation-of-a-dual-convolutional-neural","title":"Evaluation of a Dual Convolutional Neural Network Architecture for Object-wise Anomaly Detection in Cluttered X-ray Security Imagery","date":"2019-04-10","arxiv_id":"1904.05304","repositories_listed":0,"syntology":null},{"url":null,"slug":"next-active-object-prediction-from-egocentric","title":"Next-Active-Object prediction from Egocentric Videos","date":"2019-04-10","arxiv_id":"1904.05250","repositories_listed":0,"syntology":null},{"url":null,"slug":"boltvos-box-level-tracking-for-video-object","title":"BoLTVOS: Box-Level Tracking for Video Object Segmentation","date":"2019-04-09","arxiv_id":"1904.04552","repositories_listed":0,"syntology":null},{"url":null,"slug":"embodied-visual-recognition","title":"Embodied Visual Recognition","date":"2019-04-09","arxiv_id":"1904.04404","repositories_listed":0,"syntology":null}],"record_sha256":"6a027c5e48fb78d06e63306ccbfc826b96ac47d4019ec7e476cc53f13d675453","record_changed_at":"2026-09-28","record_changed_at_basis":"first_hashed"}