[CVPR2024 Highlight]GLEE: General Object Foundation Model for Images and Videos at Scale

Creating multimodal multitask models

Image Instance Segmentation - Zero Shot - OpenAI's CLIP + Meta's SAM

Official code for our paper "Enhancing Novel Object Detection via Cooperative Foundational Models"

A curated list of papers, datasets and resources pertaining to zero-shot object detection.

Resolving semantic confusions for improved zero-shot detection (BMVC 2022)

Use Grounding DINO, Segment Anything, and CLIP to label objects in images.

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

[CVPR2024] Official repository of the paper "The devil is in the fine-grained details: Evaluating open-vocabulary object detectors for fine-grained understanding."

EfficientSAM + YOLO World base model for use with Autodistill.

YOLO World base module for use with Autodistill.

OWLv2 base model for use with Autodistill.

Generate an image collage with computer vision.

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.

CoDet base model for use with Autodistill.

CLIP based Zero Shot Instance Segmentation

Qwen-VL base model for use with Autodistill.

Pranav's code contribution during his internship at ARL-W. Includes gaze-based object detection GUI and screen tracking script.