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cs.CV2022★ 1 cited
Unsupervised Flow Refinement near Motion Boundaries
Shuzhi Yu, Hannah Halin Kim, Shuai Yuan +1
Unsupervised optical flow estimators based on deep learning have attracted increasing attention due to the cost and difficulty of annotating for ground truth. Although performance…
cs.CV2022
Cross-Attention Transformer for Video Interpolation
Hannah Halin Kim, Shuzhi Yu, Shuai Yuan +1
We propose TAIN (Transformers and Attention for video INterpolation), a residual neural network for video interpolation, which aims to interpolate an intermediate frame given two c…
cs.CV2022★ 1 cited
Optical Flow Training under Limited Label Budget via Active Learning
Shuai Yuan, Xian Sun, Hannah Kim +2
Supervised training of optical flow predictors generally yields better accuracy than unsupervised training. However, the improved performance comes at an often high annotation cost…