ShuangLI59/person_search
Joint Detection and Identification Feature Learning for Person Search
This project helps security and surveillance professionals quickly locate specific individuals within a video feed or image database. It takes raw video or images as input and outputs bounding boxes around detected people along with their identified unique features, making it easier to track someone across different cameras or times. This is ideal for security analysts, law enforcement, or anyone needing to find and follow people in visual data.
755 stars. No commits in the last 6 months.
Use this if you need to automatically detect and identify individuals in large volumes of visual data, such as security footage or photo archives, to locate specific people.
Not ideal if you're looking for a simple, out-of-the-box solution without deep learning infrastructure, as it requires Caffe, specific CUDA, and MPI setups.
Stars
755
Forks
240
Language
Python
License
—
Category
Last pushed
Apr 26, 2024
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/computer-vision/ShuangLI59/person_search"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related tools
VlSomers/bpbreid
[WACV23] A strong baseline for body part-based person re-identification
VlSomers/keypoint_promptable_reidentification
[ECCV24] Keypoint Promptable Re-Identification: SOTA ReID method robust to occlusions and...
skylab-tech/ffhqr-dataset
FFHQR -- the first large-scale retouching dataset for computer vision research.
layumi/Vehicle_reID-Collection
:red_car: the collection of vehicle re-ID papers, datasets. :red_car:
tana0101/Hip-Joint-Keypoint-Detection
A research-oriented deep learning pipeline for automatic hip joint keypoint detection,...