| Title | Repo | Paper | Video |
|---|---|---|---|
| Uncovering the Missing Pattern: Unified Framework Towards Trajectory Imputation and Prediction | |||
| Tracking Multiple Deformable Objects in Egocentric Videos | |||
| Tracking through Containers and Occluders in the Wild | |||
| TarViS: A Unified Approach for Target-based Video Segmentation | |||
| VideoTrack: Learning to Track Objects via Video Transformer | |||
| ARKitTrack: A New Diverse Dataset for Tracking using Mobile RGB-D Data | |||
| A Dynamic Multi-Scale Voxel Flow Network for Video Prediction | |||
| Representation Learning for Visual Object Tracking by Masked Appearance Transfer | |||
| EqMotion: Equivariant Multi-Agent Motion Prediction with Invariant Interaction Reasoning | |||
| Semi-Supervised Video Inpainting with Cycle Consistency Constraints | |||
| Generalized Relation Modeling for Transformer Tracking | |||
Breaking the Object in Video Object Segmentation |
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| Unifying Short and Long-Term Tracking with Graph Hierarchies | |||
| Simple Cues Lead to a Strong Multi-Object Tracker | |||
| Unified Mask Embedding and Correspondence Learning for Self-Supervised Video Segmentation | |||
| MOTRv2: Bootstrapping End-to-End Multi-Object Tracking by Pretrained Object Detectors | |||
| SeqTrack: Sequence to Sequence Learning for Visual Object Tracking | |||
| Joint Visual Grounding and Tracking with Natural Language Specification | |||
| Boosting Video Object Segmentation via Space-Time Correspondence Learning | |||
| Visual Prompt Multi-Modal Tracking | |||
| OVTrack: Open-Vocabulary Multiple Object Tracking | |||
| TransFlow: Transformer as Flow Learner | |||
| Focus on Details: Online Multi-Object Tracking with Diverse Fine-grained Representation | |||
| Autoregressive Visual Tracking | |||
| Bootstrapping Objectness from Videos by Relaxed Common Fate and Visual Grouping | |||
| Tangentially Elongated Gaussian Belief Propagation for Event-based Incremental Optical Flow Estimation | |||
| Bridging Search Region Interaction with Template for RGB-T Tracking | |||
| Efficient RGB-T Tracking via Cross-Modality Distillation | |||
| MotionTrack: Learning Robust Short-Term and Long-Term Motions for Multi-Object Tracking | |||
| Self-Supervised AutoFlow | |||
| UTM: A Unified Multiple Object Tracking Model with Identity-Aware Feature Enhancement | |||
| BiFormer: Learning Bilateral Motion Estimation via Bilateral Transformer for 4K Video Frame Interpolation | |||
| Spatial-then-Temporal Self-Supervised Learning for Video Correspondence | |||
| BundleSDF: Neural 6-DoF Tracking and 3D Reconstruction of Unknown Objects | |||
| MED-VT: Multiscale Encoder-Decoder Video Transformer with Application to Object Segmentation | |||
| Context-Aware Relative Object Queries to Unify Video Instance and Panoptic Segmentation | |||
| Unsupervised Space-Time Network for Temporally-Consistent Segmentation of Multiple Motions | |||
| Resource-Efficient RGBD Aerial Tracking | |||
| MMVC: Learned Multi-Mode Video Compression with Block-based Prediction Mode Selection and Density-Adaptive Entropy Coding | |||
| Streaming Video Model | |||
| Weakly Supervised Class-Agnostic Motion Prediction for Autonomous Driving | |||
| LSTFE-Net: Long Short-Term Feature Enhancement Network for Video Small Object Detection | |||
| DistractFlow: Improving Optical Flow Estimation via Realistic Distractions and Pseudo-Labeling | |||
| SCOTCH and SODA: A Transformer Video Shadow Detection Framework | |||
| ZBS: Zero-Shot Background Subtraction via Instance-Level Background Modeling and Foreground Selection | |||
| Frame-Event Alignment and Fusion Network for High Frame Rate Tracking |