66 citations · 166 across the 13 of their papers we have counts for
13 papers
Graph Convolution Based Efficient Re-Ranking for Visual Retrieval
Yuqi Zhang, Qi Qian, Hongsong Wang +3
Visual retrieval tasks such as image retrieval and person re-identification (Re-ID) aim at effectively and thoroughly searching images with similar content or the same identity. Af…
Efficient Token-Guided Image-Text Retrieval with Consistent Multimodal Contrastive Training
Chong Liu, Yuqi Zhang, Hongsong Wang +5
Image-text retrieval is a central problem for understanding the semantic relationship between vision and language, and serves as the basis for various visual and language tasks. Mo…
2nd Place Solution to Google Landmark Retrieval 2021
Zhang Yuqi, Xu Xianzhe, Chen Weihua +4
This paper presents the 2nd place solution to the Google Landmark Retrieval 2021 Competition on Kaggle. The solution is based on a baseline with training tricks from person re-iden…
Graph Convolution for Re-ranking in Person Re-identification
Yuqi Zhang, Qian Qi, Chong Liu +4
Nowadays, deep learning is widely applied to extract features for similarity computation in person re-identification (re-ID) and have achieved great success. However, due to the no…
An Empirical Study of Vehicle Re-Identification on the AI City Challenge
Hao Luo, Weihua Chen, Xianzhe Xu +7
This paper introduces our solution for the Track2 in AI City Challenge 2021 (AICITY21). The Track2 is a vehicle re-identification (ReID) task with both the real-world data and synt…
City-Scale Multi-Camera Vehicle Tracking Guided by Crossroad Zones
Chong Liu, Yuqi Zhang, Hao Luo +6
Multi-Target Multi-Camera Tracking has a wide range of applications and is the basis for many advanced inferences and predictions. This paper describes our solution to the Track 3…
1st Place Solution to ECCV-TAO-2020: Detect and Represent Any Object for Tracking
Fei Du, Bo Xu, Jiasheng Tang +3
We extend the classical tracking-by-detection paradigm to this tracking-any-object task. Solid detection results are first extracted from TAO dataset. Some state-of-the-art techniq…
1st Place Solution to VisDA-2020: Bias Elimination for Domain Adaptive Pedestrian Re-identification
Jianyang Gu, Hao Luo, Weihua Chen +6
This paper presents our proposed methods for domain adaptive pedestrian re-identification (Re-ID) task in Visual Domain Adaptation Challenge (VisDA-2020). Considering the large gap…
3DPVNet: Patch-level 3D Hough Voting Network for 6D Pose Estimation
Yuanpeng Liu, Jun Zhou, Yuqi Zhang +2
In this paper, we focus on estimating the 6D pose of objects in point clouds. Although the topic has been widely studied, pose estimation in point clouds remains a challenging prob…
Placepedia: Comprehensive Place Understanding with Multi-Faceted Annotations
Huaiyi Huang, Yuqi Zhang, Qingqiu Huang +3
Place is an important element in visual understanding. Given a photo of a building, people can often tell its functionality, e.g. a restaurant or a shop, its cultural style, e.g. A…
Multi-Domain Learning and Identity Mining for Vehicle Re-Identification
Shuting He, Hao Luo, Weihua Chen +5
This paper introduces our solution for the Track2 in AI City Challenge 2020 (AICITY20). The Track2 is a vehicle re-identification (ReID) task with both the real-world data and synt…
From Trailers to Storylines: An Efficient Way to Learn from Movies
Qingqiu Huang, Yuanjun Xiong, Yu Xiong +2
The millions of movies produced in the human history are valuable resources for computer vision research. However, learning a vision model from movie data would meet with serious d…
Detecting Visual Relationships with Deep Relational Networks
Bo Dai, Yuqi Zhang, Dahua Lin
Relationships among objects play a crucial role in image understanding. Despite the great success of deep learning techniques in recognizing individual objects, reasoning about the…