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Found 4 papers, 3 papers with code
Video Frame Interpolation with Flow Transformer
Specifically, we design a Flow Transformer Block that calculates the temporal self-attention in a matched local area with the guidance of flow, making our framework suitable for interpolating frames with large motion while maintaining reasonably low complexity.
IncepFormer: Efficient Inception Transformer with Pyramid Pooling for Semantic Segmentation
Semantic segmentation usually benefits from global contexts, fine localisation information, multi-scale features, etc.
Ranked #378 on
Image Classification
on ImageNet
Video Frame Interpolation Based on Deformable Kernel Region
In order to solve this problem, we revisit the deformable convolution for video interpolation, which can break the fixed grid restrictions on the kernel region, making the distribution of reference points more suitable for the shape of the object, and thus warp a more accurate interpolation frame.
Dilated convolutional neural network-based deep reference picture generation for video compression
Motion estimation and motion compensation are indispensable parts of inter prediction in video coding.
