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Found 3 papers, 2 papers with code
OneVOS: Unifying Video Object Segmentation with All-in-One Transformer Framework
Contemporary Video Object Segmentation (VOS) approaches typically consist stages of feature extraction, matching, memory management, and multiple objects aggregation.
Weakly-Supervised Salient Object Detection Using Point Supervision
Then we develop a transformer-based point-supervised saliency detection model to produce the first round of saliency maps.
Attribute Surrogates Learning and Spectral Tokens Pooling in Transformers for Few-shot Learning
To improve data efficiency, we propose hierarchically cascaded transformers that exploit intrinsic image structures through spectral tokens pooling and optimize the learnable parameters through latent attribute surrogates.
Ranked #1 on
Few-Shot Learning
on Mini-ImageNet - 1-Shot Learning
