Papers Optical Flow Estimation
“Optical Flow Estimation” 태그가 달린 논문 2,218편 · 필터 해제
FreeFlow: A Bias-free Hierarchical Transformer for Optical Flow Estimation
Optical flow methods typically rely on task-specific inductive biases, such as correlation volumes, feature warping, and iterative refinement, among others, to reach high accuracy. While effective, such biases constrain …
Optical Flow EstimationLossy Event Compression: From Event Stream Distortion to Task Performance
Event cameras generate asynchronous, sparse data streams with microsecond temporal resolution, but in moderate-to-high motion scenes they can produce as many as hundreds of millions of events per second, creating signifi…
Optical Flow EstimationVideo ReconstructionObject DetectionPhysically Real-time Infrared Attack against Optical Flow Estimation Networks
With the promising performance of deep neural networks on image-based tasks, different real-world applications such as autonomous driving and motion detection have become increasingly mature and relevant to human lives. …
Optical Flow EstimationAutonomous DrivingMotion DetectionAnticipatory Risk-Guided Reinforcement Learning for Safe Flight Through Dynamic Clutter
Safe quadrotor navigation in cluttered and dynamic environments depends not only on instantaneous geometric perception, but more critically on anticipating collision risks induced by relative motion. Conventional modular…
Optical Flow EstimationReinforcement LearningObject TrackingOn the Real-World Generalisability of Optical Flow Models
Real-world deployment of vision models to broadly benefit society is arguably a main research objective. In optical flow, however, the difficulty to obtain the ground truth has focused research mainly on synthetic data a…
Optical Flow EstimationFlowPainter: Inpainting Optical Flow via Confidence-Guided Completion
Existing optical flow methods broadly follow two paradigms: iterative optimization and diffusion-based estimation. Iterative methods, exemplified by RAFT, achieve high accuracy through recurrent refinement, but remain ch…
Optical Flow EstimationTemporally Consistent Label Interpolation for Robust Surgical Multi-Task Learning under Challenging Conditions
Effective multi-task learning for surgical scene understanding is fundamentally hindered by annotation granularity mismatch; temporal workflow tasks such as phase recognition, step recognition and anticipation benefit fr…
Surgical phase recognitionOptical Flow EstimationRepresentation LearningMulti-Task LearningFracEvent: Event-Camera Simulation via Fractional-Relaxation Pixel Dynamics
Event cameras asynchronously report brightness changes with microsecond-level temporal resolution, but real event data remain difficult to collect at scale because specialized sensors, careful synchronization, and task-s…
Optical Flow EstimationImage ReconstructionEvent-based visionHiMem-WAM: Hierarchical Memory-Gated World Action Models for Robotic Manipulation
World Action Models (WAMs) have emerged as a new powerful paradigm for embodied intelligence, learning action-relevant visual dynamics that significantly enhance generalization and robustness. However, existing WAMs stil…
Optical Flow EstimationCausal InferenceFrom Contrast to Consistency: Rethinking Event-based Continuous-Time Optical Flow Estimation
Estimating continuous optical flow is a fundamental yet challenging problem in dynamic visual perception. Event-based cameras, with microsecond latency and high dynamic range, capture brightness changes asynchronously, o…
Optical Flow EstimationFlow Augmentation and Knowledge Distillation for Lightweight Face Presentation Attack Detection
Face presentation attack detection (FacePAD) remains challenging under diverse spoofing representation, including 2D print and replay, 3D mask-based spoofing, makeup-induced appearance manipulation, and physical occlusio…
Face Presentation Attack DetectionOptical Flow EstimationKnowledge DistillationLatentBurst: A Fast and Efficient Multi Frame Super-Resolution for Hexadeca-Bayer Pattern CIS images
This paper introduces a novel multi frame super-resolution network (MFSR) for burst hexadeca Bayer pattern Contact Image Sensor (CIS) images, which includes demosaicing, denoising, multi-frame fusion, and super-resolutio…
Optical Flow EstimationKnowledge DistillationU$^{2}$Flow: Uncertainty-Aware Unsupervised Optical Flow Estimation
Unsupervised optical flow methods typically lack reliable uncertainty estimation, limiting their robustness and interpretability. We propose U$^{2}$Flow, the first recurrent unsupervised framework that jointly estimates …
Optical Flow EstimationDo vision models perceive illusory motion in static images like humans?
Understanding human motion processing is essential for building reliable, human-centered computer vision systems. Although deep neural networks (DNNs) achieve strong performance in optical flow estimation, they remain le…
Optical Flow EstimationFlowIt: Global Matching via Hierarchical Transformers and Optimal Transport for Optical Flow
We present FlowIt, a novel architecture for optical flow estimation that combines global matching with confidence and occlusion-guided refinement. At its core, FlowIt leverages a hierarchical transformer architecture tha…
Zero-shot GeneralizationOptical Flow EstimationDA-Flow: Degradation-Aware Optical Flow Estimation with Diffusion Models
Optical flow models trained on high-quality data often degrade severely when confronted with real-world corruptions such as blur, noise, and compression artifacts. To overcome this limitation, we formulate Degradation-Aw…
Optical Flow EstimationImage RestorationGenOpticalFlow: A Generative Approach to Unsupervised Optical Flow Learning
Optical flow estimation is a fundamental problem in computer vision, yet the reliance on expensive ground-truth annotations limits the scalability of supervised approaches. Although unsupervised and semi-supervised metho…
Optical Flow EstimationDepth EstimationMambaVF: State Space Model for Efficient Video Fusion
Video fusion is a fundamental technique in various video processing tasks. However, existing video fusion methods heavily rely on optical flow estimation and feature warping, resulting in severe computational overhead an…
Optical Flow EstimationCoWTracker: Tracking by Warping instead of Correlation
Dense point tracking is a fundamental problem in computer vision, with applications ranging from video analysis to robotic manipulation. State-of-the-art trackers typically rely on cost volumes to match features across f…
Optical Flow EstimationPoint TrackingSRFlow: A Dataset and Regularization Model for High-Resolution Facial Optical Flow via Splatting Rasterization
Facial optical flow supports a wide range of tasks in facial motion analysis. However, the lack of high-resolution facial optical flow datasets has hindered progress in this area. In this paper, we introduce Splatting Ra…
Micro-Expression RecognitionOptical Flow Estimation