{"total":122,"rows":[{"id":"2104.02409","title":"Learning to Estimate Hidden Motions with Global Motion Aggregation","created":"2021-04-06","cited_by_count":224,"area":null},{"id":"2211.10408","title":"CroCo v2: Improved Cross-view Completion Pre-training for Stereo Matching and Optical Flow","created":"2022-11-18","cited_by_count":166,"area":null},{"id":"2108.10552","title":"E-RAFT: Dense Optical Flow from Event Cameras","created":"2021-08-24","cited_by_count":152,"area":null},{"id":"2104.07658","title":"Self-supervised Video Object Segmentation by Motion Grouping","created":"2021-04-15","cited_by_count":147,"area":null},{"id":"2410.11831","title":"CoTracker3: Simpler and Better Point Tracking by Pseudo-Labelling Real Videos","created":"2024-10-15","cited_by_count":128,"area":null},{"id":"2402.00847","title":"BootsTAP: Bootstrapped Training for Tracking-Any-Point","created":"2024-02-01","cited_by_count":120,"area":null},{"id":"2205.14620","title":"IFRNet: Intermediate Feature Refine Network for Efficient Frame Interpolation","created":"2022-05-29","cited_by_count":109,"area":null},{"id":"2104.14544","title":"AutoFlow: Learning a Better Training Set for Optical Flow","created":"2021-04-29","cited_by_count":102,"area":null},{"id":"2203.16896","title":"CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flow","created":"2022-03-31","cited_by_count":82,"area":null},{"id":"2303.08340","title":"VideoFlow: Exploiting Temporal Cues for Multi-frame Optical Flow Estimation","created":"2023-03-15","cited_by_count":82,"area":null},{"id":"2109.13912","title":"PDC-Net+: Enhanced Probabilistic Dense Correspondence Network","created":"2021-09-28","cited_by_count":80,"area":null},{"id":"2105.07014","title":"SMURF: Self-Teaching Multi-Frame Unsupervised RAFT with Full-Image Warping","created":"2021-05-14","cited_by_count":74,"area":null},{"id":"2211.09078","title":"Learning Dense and Continuous Optical Flow from an Event Camera","created":"2022-11-16","cited_by_count":60,"area":null},{"id":"2102.02629","title":"Learning Monocular Depth in Dynamic Scenes via Instance-Aware Projection Consistency","created":"2021-02-04","cited_by_count":58,"area":null},{"id":"2103.05121","title":"Multiple Instance Captioning: Learning Representations from Histopathology Textbooks and Articles","created":"2021-03-08","cited_by_count":58,"area":null},{"id":"2307.12698","title":"MC-JEPA: A Joint-Embedding Predictive Architecture for Self-Supervised Learning of Motion and Content Features","created":"2023-07-24","cited_by_count":57,"area":null},{"id":"2404.04808","title":"MemFlow: Optical Flow Estimation and Prediction with Memory","created":"2024-04-07","cited_by_count":55,"area":null},{"id":"2304.12205","title":"Synthetic Datasets for Autonomous Driving: A Survey","created":"2023-04-24","cited_by_count":48,"area":null},{"id":"2104.03308","title":"Warp Consistency for Unsupervised Learning of Dense Correspondences","created":"2021-04-07","cited_by_count":42,"area":null},{"id":"2105.08248","title":"Self-Point-Flow: Self-Supervised Scene Flow Estimation from Point Clouds with Optimal Transport and Random Walk","created":"2021-05-18","cited_by_count":39,"area":null},{"id":"2203.12870","title":"RNNPose: Recurrent 6-DoF Object Pose Refinement with Robust Correspondence Field Estimation and Pose Optimization","created":"2022-03-24","cited_by_count":38,"area":null},{"id":"2207.07522","title":"Bi-PointFlowNet: Bidirectional Learning for Point Cloud Based Scene Flow Estimation","created":"2022-07-15","cited_by_count":38,"area":null},{"id":"2201.08379","title":"Learning Pixel Trajectories with Multiscale Contrastive Random Walks","created":"2022-01-20","cited_by_count":36,"area":null},{"id":"2302.04233","title":"SkyEye: Self-Supervised Bird's-Eye-View Semantic Mapping Using Monocular Frontal View Images","created":"2023-02-08","cited_by_count":35,"area":null},{"id":"2203.10712","title":"Disentangling Architecture and Training for Optical Flow","created":"2022-03-21","cited_by_count":32,"area":null},{"id":"2203.15089","title":"Learning Optical Flow, Depth, and Scene Flow without Real-World Labels","created":"2022-03-28","cited_by_count":31,"area":null},{"id":"2412.09072","title":"Cross-View Completion Models are Zero-shot Correspondence Estimators","created":"2024-12-12","cited_by_count":30,"area":null},{"id":"2105.02216","title":"Self-Supervised Multi-Frame Monocular Scene Flow","created":"2021-05-05","cited_by_count":29,"area":null},{"id":"2110.03916","title":"Optical Flow Estimation for Spiking Camera","created":"2021-10-08","cited_by_count":29,"area":null},{"id":"2104.03965","title":"Learning optical flow from still images","created":"2021-04-08","cited_by_count":28,"area":null},{"id":"2203.07977","title":"OcclusionFusion: Occlusion-aware Motion Estimation for Real-time Dynamic 3D Reconstruction","created":"2022-03-15","cited_by_count":27,"area":null},{"id":"2203.11174","title":"DiffPoseNet: Direct Differentiable Camera Pose Estimation","created":"2022-03-21","cited_by_count":27,"area":null},{"id":"2103.02772","title":"DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images","created":"2021-03-04","cited_by_count":26,"area":null},{"id":"2103.03114","title":"Self-supervised Geometric Perception","created":"2021-03-04","cited_by_count":26,"area":null},{"id":"2202.13388","title":"PanoFlow: Learning 360{\\deg} Optical Flow for Surrounding Temporal Understanding","created":"2022-02-27","cited_by_count":26,"area":null},{"id":"2211.00882","title":"DyAnNet: A Scene Dynamicity Guided Self-Trained Video Anomaly Detection Network","created":"2022-11-02","cited_by_count":26,"area":null},{"id":"2103.10592","title":"Fusion-FlowNet: Energy-Efficient Optical Flow Estimation using Sensor Fusion and Deep Fused Spiking-Analog Network Architectures","created":"2021-03-19","cited_by_count":25,"area":null},{"id":"2104.04420","title":"SVDistNet: Self-Supervised Near-Field Distance Estimation on Surround View Fisheye Cameras","created":"2021-04-09","cited_by_count":25,"area":null},{"id":"2204.07262","title":"Imposing Consistency for Optical Flow Estimation","created":"2022-04-14","cited_by_count":24,"area":null},{"id":"2207.11075","title":"RealFlow: EM-based Realistic Optical Flow Dataset Generation from Videos","created":"2022-07-22","cited_by_count":22,"area":null},{"id":"2407.02315","title":"VFIMamba: Video Frame Interpolation with State Space Models","created":"2024-07-02","cited_by_count":22,"area":null},{"id":"2109.01097","title":"The Functional Correspondence Problem","created":"2021-09-02","cited_by_count":20,"area":null},{"id":"2308.13133","title":"AccFlow: Backward Accumulation for Long-Range Optical Flow","created":"2023-08-25","cited_by_count":19,"area":null},{"id":"2104.06789","title":"VOLDOR: Visual Odometry from Log-logistic Dense Optical flow Residuals","created":"2021-04-14","cited_by_count":17,"area":null},{"id":"2103.13725","title":"GyroFlow: Gyroscope-Guided Unsupervised Optical Flow Learning","created":"2021-03-25","cited_by_count":15,"area":null},{"id":"2204.11335","title":"Simulating Fluids in Real-World Still Images","created":"2022-04-24","cited_by_count":15,"area":null},{"id":"2206.03900","title":"Unsupervised Deformable Image Registration with Absent Correspondences in Pre-operative and Post-Recurrence Brain Tumor MRI Scans","created":"2022-06-08","cited_by_count":15,"area":null},{"id":"2210.01879","title":"A Perceptual Quality Metric for Video Frame Interpolation","created":"2022-10-04","cited_by_count":15,"area":null},{"id":"2203.05053","title":"Optical Flow Training under Limited Label Budget via Active Learning","created":"2022-03-09","cited_by_count":14,"area":null},{"id":"2207.05704","title":"M-FUSE: Multi-frame Fusion for Scene Flow Estimation","created":"2022-07-12","cited_by_count":14,"area":null},{"id":"2401.00850","title":"Refining Pre-Trained Motion Models","created":"2024-01-01","cited_by_count":12,"area":null},{"id":"2104.04724","title":"Occlusion Guided Self-supervised Scene Flow Estimation on 3D Point Clouds","created":"2021-04-10","cited_by_count":11,"area":null},{"id":"2304.07139","title":"Neuromorphic Optical Flow and Real-time Implementation with Event Cameras","created":"2023-04-14","cited_by_count":11,"area":null},{"id":"2403.18092","title":"OCAI: Improving Optical Flow Estimation by Occlusion and Consistency Aware Interpolation","created":"2024-03-26","cited_by_count":11,"area":null},{"id":"2212.01762","title":"Self-supervised AutoFlow","created":"2022-12-04","cited_by_count":10,"area":null},{"id":"2312.03102","title":"Fully Convolutional Slice-to-Volume Reconstruction for Single-Stack MRI","created":"2023-12-05","cited_by_count":10,"area":null},{"id":"2207.10314","title":"Semi-Supervised Learning of Optical Flow by Flow Supervisor","created":"2022-07-21","cited_by_count":9,"area":null},{"id":"2303.06209","title":"SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous Driving","created":"2023-03-10","cited_by_count":9,"area":null},{"id":"2303.07564","title":"Unsupervised Cumulative Domain Adaptation for Foggy Scene Optical Flow","created":"2023-03-14","cited_by_count":9,"area":null},{"id":"2506.07740","title":"Flow-Anything: Learning Real-World Optical Flow Estimation from Large-Scale Single-view Images","created":"2025-06-09","cited_by_count":9,"area":null},{"id":"2104.03560","title":"ASFlow: Unsupervised Optical Flow Learning with Adaptive Pyramid Sampling","created":"2021-04-08","cited_by_count":8,"area":null},{"id":"2106.03755","title":"HERS Superpixels: Deep Affinity Learning for Hierarchical Entropy Rate Segmentation","created":"2021-06-07","cited_by_count":8,"area":null},{"id":"2205.02031","title":"Self-Supervised Super-Resolution for Multi-Exposure Push-Frame Satellites","created":"2022-05-04","cited_by_count":8,"area":null},{"id":"2205.07399","title":"SuperWarp: Supervised Learning and Warping on U-Net for Invariant Subvoxel-Precise Registration","created":"2022-05-15","cited_by_count":8,"area":null},{"id":"2208.00776","title":"Deep 360$^\\circ$ Optical Flow Estimation Based on Multi-Projection Fusion","created":"2022-07-27","cited_by_count":8,"area":null},{"id":"2405.02608","title":"UnSAMFlow: Unsupervised Optical Flow Guided by Segment Anything Model","created":"2024-05-04","cited_by_count":8,"area":null},{"id":"2110.11680","title":"Deep Two-Stream Video Inference for Human Body Pose and Shape Estimation","created":"2021-10-22","cited_by_count":7,"area":null},{"id":"2206.03673","title":"Unsupervised Learning of 3D Scene Flow from Monocular Camera","created":"2022-06-08","cited_by_count":7,"area":null},{"id":"2306.08887","title":"SplatFlow: Learning Multi-frame Optical Flow via Splatting","created":"2023-06-15","cited_by_count":7,"area":null},{"id":"2104.03424","title":"Track, Check, Repeat: An EM Approach to Unsupervised Tracking","created":"2021-04-07","cited_by_count":6,"area":null},{"id":"2309.15110","title":"Doduo: Learning Dense Visual Correspondence from Unsupervised Semantic-Aware Flow","created":"2023-09-26","cited_by_count":6,"area":null},{"id":"2110.08805","title":"Revealing Disocclusions in Temporal View Synthesis through Infilling Vector Prediction","created":"2021-10-17","cited_by_count":5,"area":null},{"id":"2111.11141","title":"Learning Generalized Visual Odometry Using Position-Aware Optical Flow and Geometric Bundle Adjustment","created":"2021-11-22","cited_by_count":5,"area":null},{"id":"2307.06003","title":"Unsupervised Optical Flow Estimation with Dynamic Timing Representation for Spike Camera","created":"2023-07-12","cited_by_count":5,"area":null},{"id":"2404.16828","title":"Made to Order: Discovering monotonic temporal changes via self-supervised video ordering","created":"2024-04-25","cited_by_count":5,"area":null},{"id":"2406.04999","title":"ProMotion: Prototypes As Motion Learners","created":"2024-06-07","cited_by_count":5,"area":null},{"id":"2410.20752","title":"Bidirectional Recurrence for Cardiac Motion Tracking with Gaussian Process Latent Coding","created":"2024-10-28","cited_by_count":5,"area":null},{"id":"2503.06992","title":"Bridge Frame and Event: Common Spatiotemporal Fusion for High-Dynamic Scene Optical Flow","created":"2025-03-10","cited_by_count":5,"area":null},{"id":"2106.13953","title":"In-N-Out: Towards Good Initialization for Inpainting and Outpainting","created":"2021-06-26","cited_by_count":4,"area":null},{"id":"2107.10990","title":"Detail Preserving Residual Feature Pyramid Modules for Optical Flow","created":"2021-07-23","cited_by_count":4,"area":null},{"id":"2109.15321","title":"Sensor-Guided Optical Flow","created":"2021-09-30","cited_by_count":4,"area":null},{"id":"2206.10480","title":"Learning to Estimate and Refine Fluid Motion with Physical Dynamics","created":"2022-06-21","cited_by_count":4,"area":null},{"id":"2401.17642","title":"Exploring the Common Appearance-Boundary Adaptation for Nighttime Optical Flow","created":"2024-01-31","cited_by_count":4,"area":null},{"id":"2403.04071","title":"On-device Self-supervised Learning of Visual Perception Tasks aboard Hardware-limited Nano-quadrotors","created":"2024-03-06","cited_by_count":4,"area":null},{"id":"2408.03168","title":"Training on the Fly: On-device Self-supervised Learning aboard Nano-drones within 20 mW","created":"2024-08-06","cited_by_count":4,"area":null},{"id":"2409.17001","title":"Adverse Weather Optical Flow: Cumulative Homogeneous-Heterogeneous Adaptation","created":"2024-09-25","cited_by_count":4,"area":null},{"id":"2101.10777","title":"Dense Semantic Forecasting in Video by Joint Regression of Features and Feature Motion","created":"2021-01-26","cited_by_count":3,"area":null},{"id":"2107.03610","title":"NccFlow: Unsupervised Learning of Optical Flow With Non-occlusion from Geometry","created":"2021-07-08","cited_by_count":3,"area":null},{"id":"2203.02193","title":"Time-to-Label: Temporal Consistency for Self-Supervised Monocular 3D Object Detection","created":"2022-03-04","cited_by_count":3,"area":null},{"id":"2208.02305","title":"Unsupervised Flow Refinement near Motion Boundaries","created":"2022-08-03","cited_by_count":3,"area":null},{"id":"2301.03832","title":"Video Semantic Segmentation with Inter-Frame Feature Fusion and Inner-Frame Feature Refinement","created":"2023-01-10","cited_by_count":3,"area":null},{"id":"2303.13761","title":"Unsupervised Hierarchical Domain Adaptation for Adverse Weather Optical Flow","created":"2023-03-24","cited_by_count":3,"area":null},{"id":"2307.09696","title":"Towards Saner Deep Image Registration","created":"2023-07-19","cited_by_count":3,"area":null},{"id":"2403.16116","title":"Self-Supervised Multi-Frame Neural Scene Flow","created":"2024-03-24","cited_by_count":3,"area":null},{"id":"2411.14865","title":"Towards Dependable Optical Flow: Benchmarks for Real-World Spatiotemporal Corruptions","created":"2024-11-22","cited_by_count":3,"area":null},{"id":"2509.12791","title":"Superpixel Anything: A general object-based framework for accurate yet regular superpixel segmentation","created":"2025-09-16","cited_by_count":3,"area":null},{"id":"2106.11769","title":"Improving Ultrasound Tongue Image Reconstruction from Lip Images Using Self-supervised Learning and Attention Mechanism","created":"2021-06-20","cited_by_count":2,"area":null},{"id":"2212.08740","title":"Lateral Strain Imaging using Self-supervised and Physically Inspired Constraints in Unsupervised Regularized Elastography","created":"2022-12-16","cited_by_count":2,"area":null},{"id":"2304.07159","title":"Unsupervised Learning Optical Flow in Multi-frame Dynamic Environment Using Temporal Dynamic Modeling","created":"2023-04-14","cited_by_count":2,"area":null},{"id":"2404.04677","title":"Salient Sparse Visual Odometry With Pose-Only Supervision","created":"2024-04-06","cited_by_count":2,"area":null}],"next_cursor":"100"}