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Found 5 papers, 4 papers with code
Learning to Generate Image Embeddings with User-level Differential Privacy
Small on-device models have been successfully trained with user-level differential privacy (DP) for next word prediction and image classification tasks in the past.
kMaX-DeepLab: k-means Mask Transformer
However, we observe that most existing transformer-based vision models simply borrow the idea from NLP, neglecting the crucial difference between languages and images, particularly the extremely large sequence length of spatially flattened pixel features.
Ranked #2 on
Panoptic Segmentation
on COCO test-dev
CMT-DeepLab: Clustering Mask Transformers for Panoptic Segmentation
We propose Clustering Mask Transformer (CMT-DeepLab), a transformer-based framework for panoptic segmentation designed around clustering.
Ranked #6 on
Panoptic Segmentation
on COCO test-dev
STEP: Segmenting and Tracking Every Pixel
The task of assigning semantic classes and track identities to every pixel in a video is called video panoptic segmentation.
Pose2Instance: Harnessing Keypoints for Person Instance Segmentation
In a more realistic environment, without the oracle keypoints, the proposed deep person instance segmentation model conditioned on human pose achieves 3. 8% to 10. 5% relative improvements comparing with its strongest baseline of a deep network trained only for segmentation.
