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Efficient Segment Anything in Medical Images
A curated list of resources for using LLMs to develop more competitive grant applications.
Medical SAM 2: Segment Medical Images As Video Via Segment Anything Model 2
code and trained models for "Attentional Feature Fusion"
Segment Anything in Medical Images
[ICLR 2023] Official implementation of the paper "DINO: DETR with Improved DeNoising Anchor Boxes for End-to-End Object Detection"
PyTorch code for Vision Transformers training with the Self-Supervised learning method DINO
PyTorch code and models for the DINOv2 self-supervised learning method.
[ECCV 2024] Official implementation of the paper "Semantic-SAM: Segment and Recognize Anything at Any Granularity"
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 th…
Python library for YOLO small object detection and instance segmentation
Papers for CNN, object detection, keypoint detection, semantic segmentation, medical image processing, SLAM, etc.
A python library for self-supervised learning on images.
the official pytorch implementation of “Mamba-YOLO：SSMs-based for Object Detection”
Convert JSON annotations into YOLO format.
🔥🔥🔥专注于改进YOLOv8模型，NEW - YOLOv8 🚀 RT-DETR 🥇 in PyTorch >, Support to improve backbone, neck, head, loss, IoU, NMS and other modules🚀
Implement of CVPR2024 'Infrared Small Target Detection with Scale and Location Sensitivity'
StarDist - Object Detection with Star-convex Shapes
Centralized Feature Pyramid for Object Detection
Efficient vision foundation models for high-resolution generation and perception.
YOLOX is a high-performance anchor-free YOLO, exceeding yolov3~v5 with MegEngine, ONNX, TensorRT, ncnn, and OpenVINO supported. Documentation: https://yolox.readthedocs.io/