[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale
-
Updated
May 8, 2024 - Python
[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale
Creating multimodal multitask models
API for Grounding DINO 1.5: IDEA Research's Most Capable Open-World Object Detection Model Series
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
Resolving semantic confusions for improved zero-shot detection (BMVC 2022)
OWLv2 base model for use with Autodistill.
Use Grounding DINO, Segment Anything, and CLIP to label objects in images.
Official code for our paper "Enhancing Novel Object Detection via Cooperative Foundational Models"
[CVPR2024] Official repository of the paper "The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding."
Image Instance Segmentation - Zero Shot - OpenAI's CLIP + Meta's SAM
Use PaliGemma to auto-label data for use in training fine-tuned vision models.
CLIP based Zero Shot Instance Segmentation
Generate an image collage with computer vision.
EfficientSAM + YOLO World base model for use with Autodistill.
This project represents a GroundingDINO Inference (zero-shot object detection) procedure with both methods (CLI and Script). This implementation will help the reader to know the sequence of commands and exemplifying commands for running a quick zero-shot object detection. Additionally, the reader may get insight into code (script) execution.
YOLO World base module for use with Autodistill.
A curated list of papers, datasets and resources pertaining to zero-shot object detection.
CoDet base model for use with Autodistill.
Qwen-VL base model for use with Autodistill.
Add a description, image, and links to the zero-shot-object-detection topic page so that developers can more easily learn about it.
To associate your repository with the zero-shot-object-detection topic, visit your repo's landing page and select "manage topics."