pasqualedem/LabelAnything

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

This is the official implementation of the ECCV'2022 paper "Dense Cross-Query-and-Support Attention Weighted Mask Aggregation for Few-Shot Segmentation".

[NeurIPS 2023] Official implementation of the paper "Segment Everything Everywhere All at Once"

The repository provides code for running inference with the SegmentAnything Model (SAM), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

Official code for "No time to train! Training-Free Reference-Based Instance Segmentation"

The repository provides code for running inference and finetuning with the Meta Segment Anything Model 3 (SAM 3), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

[AAAI 2025] Official PyTorch implementation of "TinySAM: Pushing the Envelope for Efficient Segment Anything Model"

The repository provides code for running inference with the Meta Segment Anything Model 2 (SAM 2), links for downloading the trained model checkpoints, and example notebooks that show how to use the model.

[ECCV2024] ProxyCLIP: Proxy Attention Improves CLIP for Open-Vocabulary Segmentation