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Optical Flow Estimation On Kitti 2015 Train

评估指标

EPE
F1-all

评测结果

各个模型在此基准测试上的表现结果

模型名称
EPE
F1-all
Paper TitleRepository
VCN8.3625.1Volumetric Correspondence Networks for Optical Flow
CRAFT4.8817.5CRAFT: Cross-Attentional Flow Transformer for Robust Optical Flow-
RAFT5.0417.4RAFT: Recurrent All-Pairs Field Transforms for Optical Flow-
PWC-Net10.3533.7PWC-Net: CNNs for Optical Flow Using Pyramid, Warping, and Cost Volume-
FastFlowNet12.2433.1FastFlowNet: A Lightweight Network for Fast Optical Flow Estimation-
GMA4.6917.1Learning to Estimate Hidden Motions with Global Motion Aggregation-
FlowNet210.0830.0FlowNet 2.0: Evolution of Optical Flow Estimation with Deep Networks-
FlowFormer4.0914.7FlowFormer: A Transformer Architecture for Optical Flow-
HD313.1724.0Hierarchical Discrete Distribution Decomposition for Match Density Estimation-
Ef-RAFT4.8316.45Rethinking RAFT for Efficient Optical Flow-
RPKNet3.7913.0Recurrent Partial Kernel Network for Efficient Optical Flow Estimation
RAPIDFlow5.8717.7RAPIDFlow: Recurrent Adaptable Pyramids with Iterative Decoding for Efficient Optical Flow Estimation
DEQ-Flow3.7613.0Deep Equilibrium Optical Flow Estimation-
GMFlowNet4.2415.4Global Matching with Overlapping Attention for Optical Flow Estimation-
MaskFlowNet-23.1MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask-
SCV6.8019.3Learning Optical Flow from a Few Matches-
SeparableFlow4.6015.9Separable Flow: Learning Motion Cost Volumes for Optical Flow Estimation
DPFlow3.3711.1DPFlow: Adaptive Optical Flow Estimation with a Dual-Pyramid Framework-
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Optical Flow Estimation On Kitti 2015 Train | SOTA | HyperAI超神经