open-vocabulary-detection

Grounded SAM: Marrying Grounding DINO with Segment Anything & Stable Diffusion & Recognize Anything - Automatically Detect , Segment and Generate Anything

#计算机科学#A collection of tutorials on state-of-the-art computer vision models and techniques. Explore everything from foundational architectures like ResNet to cutting-edge models like YOLO11, RT-DETR, SAM 2, ...

#大语言模型#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

#自然语言处理#👁️ + 💬 + 🎧 = 🤖 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

#Awesome#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 w...

[AAAI'25] Official Code for “Locate Anything on Earth: Advancing Open-Vocabulary Object Detection for Remote Sensing Community"

[CVPR2024] Generative Region-Language Pretraining for Open-Ended 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).

(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

#计算机科学#[WACV 2025] Official code for our paper "Enhancing Novel Object Detection via Cooperative Foundational Models"

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

#计算机科学#[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.

A Comprehensive Evaluation Benchmark for Open-Vocabulary Detection (AAAI 2024)

Make Large Multimodal Models excel in object detection, ICCV 2025