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Found 2 papers, 2 papers with code
Sparse DETR: Efficient End-to-End Object Detection with Learnable Sparsity
Deformable DETR uses the multiscale feature to ameliorate performance, however, the number of encoder tokens increases by 20x compared to DETR, and the computation cost of the encoder attention remains a bottleneck.
Spatially Consistent Representation Learning
While these contrastive methods mainly focus on generating invariant global representations at the image-level under semantic-preserving transformations, they are prone to overlook spatial consistency of local representations and therefore have a limitation in pretraining for localization tasks such as object detection and instance segmentation.
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