Optical Flow Estimation
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Benchmarks
Sintel-clean
Sintel-final
KITTI 2015 (train)
KITTI 2015
KITTI 2012
Spring
KITTI 2015 unsupervised
KITTI 2012 unsupervised
Most implemented
PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume
FlowNet: Learning Optical Flow with Convolutional Networks
RAFT: Recurrent All-Pairs Field Transforms for Optical Flow
RIFE: Real-Time Intermediate Flow Estimation for Video Frame Interpolation
FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks
Perceiver IO: A General Architecture for Structured Inputs & Outputs
Papers
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 Estimation