songtianhui/SimpleSeg

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.

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.

WeVisOne-VL is a powerful VLM by the WeChat Vision Team at Tencent, unifying object-level and pixel-level perception from points and boxes to masks and alpha mattes.

[NeurIPS 2024] SlimSAM: 0.1% Data Makes Segment Anything Slim

EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything

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.

[Technical Report] Locate, Segment, and Reason.

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

[ECCV 2024] SAM4MLLM: Enhance Multi-Modal Large Language Model for Referring Expression Segmentation