Search Results for author:
Found 6 papers, 5 papers with code
Beyond Appearance: a Semantic Controllable Self-Supervised Learning Framework for Human-Centric Visual Tasks
Unlike the existing self-supervised learning methods, prior knowledge from human images is utilized in SOLIDER to build pseudo semantic labels and import more semantic information into the learned representation.
Ranked #1 on
Person Search
on PRW
DAMO-YOLO : A Report on Real-Time Object Detection Design
Based on these new techs, we build a suite of models at various scales to meet the needs of different scenarios.
Ranked #33 on
Real-Time Object Detection
on MS COCO
TransFGU: A Top-down Approach to Fine-Grained Unsupervised Semantic Segmentation
Unsupervised semantic segmentation aims to obtain high-level semantic representation on low-level visual features without manual annotations.
Ranked #2 on
Unsupervised Semantic Segmentation
on COCO-Stuff-171
(using extra training data)
Achieving Human Parity on Visual Question Answering
The Visual Question Answering (VQA) task utilizes both visual image and language analysis to answer a textual question with respect to an image.
Ranked #7 on
Visual Question Answering (VQA)
on VQA v2 test-dev
An Empirical Study of Vehicle Re-Identification on the AI City Challenge
We mainly focus on four points, i. e. training data, unsupervised domain-adaptive (UDA) training, post-processing, model ensembling in this challenge.
City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones
Multi-Target Multi-Camera Tracking has a wide range of applications and is the basis for many advanced inferences and predictions.
