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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
This is a list of awesome paper about optical flow and related work.
| Date | Stars |
|---|---|
| 2026-07-24 | 651 |
| 2026-07-25 | 651 |
| 2026-07-28 | 651 |
| 2026-07-30 | 651 |
| 2026-08-06 | 651 |
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# Awesome-Optical-Flow This is a list of awesome articles about optical flow and related work. [Click here to read in full screen.](https://github.com/hzwer/Awesome-Optical-Flow/blob/main/README.md) The table of contents is on the right side of the "README.md". Recently, I write [A Survey on Future Frame Synthesis: Bridging Deterministic and Generative Approaches](https://arxiv.org/pdf/2401.14718 ), welcome to read. ## Optical Flow ### Supervised Models | Time | Paper | Repo | | -------- | -------- | -------- | |CVPR24|[MemFlow: Optical Flow Estimation and Prediction with Memory](https://dqiaole.github.io/MemFlow/)|[MemFlow](https://github.com/DQiaole/MemFlow) | |CVPR23|[DistractFlow: Improving Optical Flow Estimation via Realistic Distractions and Pseudo-Labeling](https://arxiv.org/abs/2303.14078) |CVPR23|[Masked Cost Volume Autoencoding for Pretraining Optical Flow Estimation](https://openaccess.thecvf.com/content/CVPR2023/html/Shi_FlowFormer_Masked_Cost_Volume_Autoencoding_for_Pretraining_Optical_Flow_Estimation_CVPR_2023_paper.html)|[FlowFormerPlusPlus](https://github.com/XiaoyuShi97/FlowFormerPlusPlus) | |NeurIPS22|[SKFlow: Learning Optical Flow with Super Kernels](https://openreview.net/forum?id=v2es9YoukWO)|[SKFlow](https://github.com/littlespray/SKFlow) | |ECCV22|[Disentangling architecture and training for optical flow](https://arxiv.org/abs/2203.10712)|[Autoflow](https://github.com/google-research/opticalflow-autoflow) | |ECCV22|[FlowFormer: A Transformer Architecture for Optical Flow](https://arxiv.org/pdf/2203.16194.pdf)|[FlowFormer](https://github.com/drinkingcoder/FlowFormer-Official/) | |CVPR22|[Learning Optical Flow with Kernel Patch Attention](https://openaccess.thecvf.com/content/CVPR2022/papers/Luo_Learning_Optical_Flow_With_Kernel_Patch_Attention_CVPR_2022_paper.pdf)|[KPAFlow](https://github.com/megvii-research/KPAFlow) | |CVPR22|[GMFlow: Learning Optical Flow via Global Matching](https://arxiv.org/abs/2111.13680)|[gmflow](https://github.com/haofeixu/gmflow) | |CVPR22|[Deep Equilibrium Optical Flow Estimation](https://arxiv.org/pdf/2204.08442.pdf)|[deq-flow](https://github.com/locuslab/deq-flow) | |ICCV21|[High-Resolution Optical Flow from 1D Attention and Correlation](https://arxiv.org/abs/2104.13918)|[flow1d](https://github.com/haofeixu/flow1d)| |ICCV21|[Learning to Estimate Hidden Motions with Global Motion Aggregation](https://arxiv.org/abs/2104.02409)|[GMA](https://github.com/zacjiang/GMA) | |CVPR21|[Learning Optical Flow from a Few Matches](https://arxiv.org/abs/2104.02166)|[SCV](https://github.com/zacjiang/SCV) | |TIP21|[Detail Preserving Coarse-to-Fine Matching for Stereo Matching and Optical Flow](https://ieeexplore.ieee.org/document/9459444) |ECCV20|[RAFT: Recurrent All Pairs Field Transforms for Optical Flow](https://arxiv.org/pdf/2003.12039.pdf)|[RAFT](https://github.com/princeton-vl/RAFT)  |CVPR20|[MaskFlownet: Asymmetric Feature Matching with Learnable Occlusion Mask](https://arxiv.org/abs/2003.10955)|[MaskFlownet](https://github.com/microsoft/MaskFlownet) 
hzwer · @stepfun-ai
109
Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:79748694fc32483e, topic:computer-vision, name:optical flow, desc:optical flow
matched fp:79748694fc32483e, topic:deep-learning, readme:pretraining