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Found 3 papers, 2 papers with code
Polarized Self-Attention: Towards High-quality Pixel-wise Regression
Pixel-wise regression is probably the most common problem in fine-grained computer vision tasks, such as estimating keypoint heatmaps and segmentation masks.
Ranked #2 on
Keypoint Detection
on MS COCO
(Validation AP metric)
CrackFormer: Transformer Network for Fine-Grained Crack Detection
The CrackFormer is composed of novel attention modules in a SegNet-like encoder-decoder architecture.
DeepDA: LSTM-based Deep Data Association Network for Multi-Targets Tracking in Clutter
The Long Short-Term Memory (LSTM) neural network based data association algorithm named as DeepDA for multi-target tracking in clutters is proposed to deal with the NP-hard combinatorial optimization problem in this paper.
