{"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":"2111.13680","title":"GMFlow: Learning Optical Flow via Global Matching","created":"2021-11-26","cited_by_count":327,"area":null},{"id":"2203.16194","title":"FlowFormer: A Transformer Architecture for Optical Flow","created":"2022-03-30","cited_by_count":275,"area":null},{"id":"2211.05783","title":"Unifying Flow, Stereo and Depth Estimation","created":"2022-11-10","cited_by_count":275,"area":null},{"id":"2304.09790","title":"AMT: All-Pairs Multi-Field Transforms for Efficient Frame Interpolation","created":"2023-04-19","cited_by_count":180,"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":"2205.14623","title":"SKFlow: Learning Optical Flow with Super Kernels","created":"2022-05-29","cited_by_count":56,"area":null},{"id":"2203.13674","title":"Dense Continuous-Time Optical Flow from Events and Frames","created":"2022-03-25","cited_by_count":46,"area":null},{"id":"2210.01794","title":"Implicit Warping for Animation with Image Sets","created":"2022-10-04","cited_by_count":45,"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":"2203.10712","title":"Disentangling Architecture and Training for Optical Flow","created":"2022-03-21","cited_by_count":32,"area":null},{"id":"2303.11629","title":"TMA: Temporal Motion Aggregation for Event-based Optical Flow","created":"2023-03-21","cited_by_count":32,"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":"2503.14880","title":"DPFlow: Adaptive Optical Flow Estimation with a Dual-Pyramid Framework","created":"2025-03-19","cited_by_count":30,"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":"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":"2202.00909","title":"CSFlow: Learning Optical Flow via Cross Strip Correlation for Autonomous Driving","created":"2022-02-02","cited_by_count":16,"area":null},{"id":"2303.14078","title":"DistractFlow: Improving Optical Flow Estimation via Realistic Distractions and Pseudo-Labeling","created":"2023-03-24","cited_by_count":14,"area":null},{"id":"2403.17931","title":"Track Everything Everywhere Fast and Robustly","created":"2024-03-26","cited_by_count":14,"area":null},{"id":"2212.01762","title":"Self-supervised AutoFlow","created":"2022-12-04","cited_by_count":10,"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":"2303.06209","title":"SemARFlow: Injecting Semantics into Unsupervised Optical Flow Estimation for Autonomous Driving","created":"2023-03-10","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":"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":"2207.13297","title":"GPS-GLASS: Learning Nighttime Semantic Segmentation Using Daytime Video and GPS data","created":"2022-07-27","cited_by_count":7,"area":null},{"id":"2306.05691","title":"DIFT: Dynamic Iterative Field Transforms for Memory Efficient Optical Flow","created":"2023-06-09","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":"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":"2404.17621","title":"Attention-aware non-rigid image registration for accelerated MR imaging","created":"2024-04-26","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":"2401.05879","title":"YOIO: You Only Iterate Once by mining and fusing multiple necessary global information in the optical flow estimation","created":"2024-01-11","cited_by_count":1,"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":"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":"2212.10174","title":"CGCV:Context Guided Correlation Volume for Optical Flow Neural Networks","created":"2022-12-20","cited_by_count":0,"area":null},{"id":"2302.03873","title":"Geometric Perception based Efficient Text Recognition","created":"2023-02-08","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":"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":"2412.13273","title":"CompactFlowNet: Efficient Real-time Optical Flow Estimation on Mobile Devices","created":"2024-12-17","cited_by_count":0,"area":null},{"id":"2508.09743","title":"HKT: A Biologically Inspired Framework for Modular Hereditary Knowledge Transfer in Neural Networks","created":"2025-08-13","cited_by_count":0,"area":null},{"id":"2605.29220","title":"Motion-guided sparse correction enables expert-quality point tracking across diverse microscopy regimes","created":"2026-05-28","cited_by_count":0,"area":null}],"next_cursor":null}