Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
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Updated
Sep 5, 2024 - Jupyter Notebook
Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything
Examples and tutorials on using SOTA computer vision models and techniques. Learn everything from old-school ResNet, through YOLO and object-detection transformers like DETR, to the latest models like Grounding DINO and SAM.
Must-have resource for anyone who wants to experiment with and build on the OpenAI vision API 🔥
[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale
Grounding DINO 1.5: IDEA Research's Most Capable Open-World Object Detection Model Series
👁️ + 💬 + 🎧 = 🤖 Curated list of top foundation and multimodal models! [Paper + Code + Examples + Tutorials]
Combining Segment Anything (SAM) with Grounded DINO for zero-shot object detection and CLIPSeg for zero-shot segmentation
Official implementation of OV-DINO: Unified Open-Vocabulary Detection with Language-Aware Selective Fusion
A curated list of papers and resources related to Described Object Detection, Open-Vocabulary/Open-World Object Detection and Referring Expression Comprehension. Updated frequently and pull requests welcomed.
[CVPR2024] Generative Region-Language Pretraining for Open-Ended Object Detection
(NeurIPS2023) CoDet: Co-Occurrence Guided Region-Word Alignment for Open-Vocabulary Object Detection
[CVPR'24 Highlight] SHiNe: Semantic Hierarchy Nexus for Open-vocabulary Object Detection
A detection/segmentation dataset with labels characterized by intricate and flexible expressions. "Described Object Detection: Liberating Object Detection with Flexible Expressions" (NeurIPS 2023).
[WACV 2025] Official code for our paper "Enhancing Novel Object Detection via Cooperative Foundational Models"
[CVPR2024 Highlight] Official repository of the paper "The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding."
Python scripts performing Open Vocabulary Object Detection using the YOLO-World model in ONNX.
使用onnxruntime部署GroundingDINO开放世界目标检测,包含C++和Python两个版本的程序
A Comprehensive Evaluation Benchmark for Open-Vocabulary Detection (AAAI 2024)
🦕 [AAAI'25] Official Code for “Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community"
[AAAI2024] Code Release of CLIM: Contrastive Language-Image Mosaic for Region Representation
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