{"total":53,"rows":[{"id":"2307.07635","title":"CoTracker: It is Better to Track Together","created":"2023-07-14","cited_by_count":522,"area":null},{"id":"2203.16194","title":"FlowFormer: A Transformer Architecture for Optical Flow","created":"2022-03-30","cited_by_count":275,"area":null},{"id":"2407.13764","title":"Shape of Motion: 4D Reconstruction from a Single Video","created":"2024-07-18","cited_by_count":250,"area":null},{"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":"2303.01237","title":"FlowFormer++: Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation","created":"2023-03-02","cited_by_count":114,"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":"2204.08442","title":"Deep Equilibrium Optical Flow Estimation","created":"2022-04-18","cited_by_count":64,"area":null},{"id":"2205.14623","title":"SKFlow: Learning Optical Flow with Super Kernels","created":"2022-05-29","cited_by_count":56,"area":null},{"id":"2403.13042","title":"TAPTR: Tracking Any Point with Transformers as Detection","created":"2024-03-19","cited_by_count":45,"area":null},{"id":"2204.00330","title":"DIP: Deep Inverse Patchmatch for High-Resolution Optical Flow","created":"2022-04-01","cited_by_count":40,"area":null},{"id":"2202.03857","title":"Learning Optical Flow with Adaptive Graph Reasoning","created":"2022-02-08","cited_by_count":33,"area":null},{"id":"2304.11523","title":"TransFlow: Transformer as Flow Learner","created":"2023-04-23","cited_by_count":32,"area":null},{"id":"2211.13726","title":"Lightweight Event-based Optical Flow Estimation via Iterative Deblurring","created":"2022-11-24","cited_by_count":31,"area":null},{"id":"2502.13716","title":"Event-Based Video Frame Interpolation With Cross-Modal Asymmetric Bidirectional Motion Fields","created":"2025-02-19","cited_by_count":25,"area":null},{"id":"2309.16217","title":"GAFlow: Incorporating Gaussian Attention into Optical Flow","created":"2023-09-28","cited_by_count":18,"area":null},{"id":"2407.16291","title":"TAPTRv2: Attention-based Position Update Improves Tracking Any Point","created":"2024-07-23","cited_by_count":18,"area":null},{"id":"2303.16493","title":"AnyFlow: Arbitrary Scale Optical Flow with Implicit Neural Representation","created":"2023-03-29","cited_by_count":17,"area":null},{"id":"2307.16586","title":"SAMFlow: Eliminating Any Fragmentation in Optical Flow with Segment Anything Model","created":"2023-07-31","cited_by_count":15,"area":null},{"id":"2409.05688","title":"LayeredFlow: A Real-World Benchmark for Non-Lambertian Multi-Layer Optical Flow","created":"2024-09-09","cited_by_count":11,"area":null},{"id":"2207.12163","title":"Multi-Scale RAFT: Combining Hierarchical Concepts for Learning-based Optical FLow Estimation","created":"2022-07-25","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":"2312.03790","title":"Memory-Efficient Optical Flow via Radius-Distribution Orthogonal Cost Volume","created":"2023-12-06","cited_by_count":9,"area":null},{"id":"2310.17294","title":"Scale-Adaptive Feature Aggregation for Efficient Space-Time Video Super-Resolution","created":"2023-10-26","cited_by_count":8,"area":null},{"id":"2401.00833","title":"Rethinking RAFT for Efficient Optical Flow","created":"2024-01-01","cited_by_count":8,"area":null},{"id":"2411.18671","title":"TAPTRv3: Spatial and Temporal Context Foster Robust Tracking of Any Point in Long Video","created":"2024-11-27","cited_by_count":8,"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":"2403.10425","title":"NeuFlow: Real-time, High-accuracy Optical Flow Estimation on Robots Using Edge Devices","created":"2024-03-15","cited_by_count":7,"area":null},{"id":"2506.23151","title":"MEMFOF: High-Resolution Training for Memory-Efficient Multi-Frame Optical Flow Estimation","created":"2025-06-29","cited_by_count":7,"area":null},{"id":"2409.04243","title":"Hybrid Cost Volume for Memory-Efficient Optical Flow","created":"2024-09-06","cited_by_count":6,"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":"2308.07104","title":"FocusFlow: Boosting Key-Points Optical Flow Estimation for Autonomous Driving","created":"2023-08-14","cited_by_count":5,"area":null},{"id":"2107.08187","title":"SCV-Stereo: Learning Stereo Matching from a Sparse Cost Volume","created":"2021-07-17","cited_by_count":4,"area":null},{"id":"2404.17621","title":"Attention-aware non-rigid image registration for accelerated MR imaging","created":"2024-04-26","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":"2306.05442","title":"FlowFormer: A Transformer Architecture and Its Masked Cost Volume Autoencoding for Optical Flow","created":"2023-06-08","cited_by_count":3,"area":null},{"id":"2510.13317","title":"Removing Cost Volumes from Optical Flow Estimators","created":"2025-10-15","cited_by_count":3,"area":null},{"id":"2304.08101","title":"LLA-FLOW: A Lightweight Local Aggregation on Cost Volume for Optical Flow Estimation","created":"2023-04-17","cited_by_count":2,"area":null},{"id":"2404.08135","title":"SciFlow: Empowering Lightweight Optical Flow Models with Self-Cleaning Iterations","created":"2024-04-11","cited_by_count":2,"area":null},{"id":"2404.15497","title":"Deep-learning Optical Flow Outperforms PIV in Obtaining Velocity Fields from Active Nematics","created":"2024-04-23","cited_by_count":1,"area":null},{"id":"2407.10137","title":"Pattern Guided UV Recovery for Realistic Video Garment Texturing","created":"2024-07-14","cited_by_count":1,"area":null},{"id":"2503.03256","title":"BAT: Learning Event-based Optical Flow with Bidirectional Adaptive Temporal Correlation","created":"2025-03-05","cited_by_count":1,"area":null},{"id":"2505.16942","title":"Efficient All-Pairs Correlation Volume Sampling for Optical Flow Estimation","created":"2025-05-22","cited_by_count":1,"area":null},{"id":"2512.18684","title":"A Study of Finetuning Video Transformers for Multi-view Geometry Tasks","created":"2025-12-21","cited_by_count":1,"area":null},{"id":"2606.19938","title":"Triangular Consistency as a Universal Constraint for Learning Optical Flow","created":"2026-06-18","cited_by_count":1,"area":null},{"id":"2207.01271","title":"FlowNAS: Neural Architecture Search for Optical Flow Estimation","created":"2022-07-04","cited_by_count":0,"area":null},{"id":"2312.07180","title":"Context-Aware Iteration Policy Network for Efficient Optical Flow Estimation","created":"2023-12-12","cited_by_count":0,"area":null},{"id":"2405.12512","title":"Rethink Predicting the Optical Flow with the Kinetics Perspective","created":"2024-05-21","cited_by_count":0,"area":null},{"id":"2409.05531","title":"HMAFlow: Learning More Accurate Optical Flow via Hierarchical Motion Field Alignment","created":"2024-09-09","cited_by_count":0,"area":null},{"id":"2507.02307","title":"Flow-CDNet: A Novel Network for Detecting Both Slow and Fast Changes in Bitemporal Images","created":"2025-07-03","cited_by_count":0,"area":null},{"id":"2511.22459","title":"Gaussians on Fire: High-Frequency Reconstruction of Flames","created":"2025-11-27","cited_by_count":0,"area":null},{"id":"2602.05572","title":"ShapeGaussian: High-Fidelity 4D Human Reconstruction in Monocular Videos via Vision Priors","created":"2026-02-05","cited_by_count":0,"area":null},{"id":"2603.28759","title":"FlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow","created":"2026-03-30","cited_by_count":0,"area":null}],"next_cursor":null}