activity
20192021
most citedOne Million Scenes for Autonomous Driving: ONCE Dataset

133 citations · 327 across the 18 of their papers we have counts for

collaborators

28 papers

cs.CV20212 cited

ViDA-MAN: Visual Dialog with Digital Humans

Tong Shen, Jiawei Zuo, Fan Shi +7

We demonstrate ViDA-MAN, a digital-human agent for multi-modal interaction, which offers realtime audio-visual responses to instant speech inquiries. Compared to traditional text o…

cs.CV20211 cited

Video Temporal Relationship Mining for Data-Efficient Person Re-identification

Siyu Chen, Dengjie Li, Lishuai Gao +3

This paper is a technical report to our submission to the ICCV 2021 VIPriors Re-identification Challenge. In order to make full use of the visual inductive priors of the data, we t…

cs.CV2021

G-DetKD: Towards General Distillation Framework for Object Detectors via Contrastive and Semantic-guided Feature Imitation

Lewei Yao, Renjie Pi, Hang Xu +3

In this paper, we investigate the knowledge distillation (KD) strategy for object detection and propose an effective framework applicable to both homogeneous and heterogeneous stud…

cs.CV202133 cited

SODA10M: A Large-Scale 2D Self/Semi-Supervised Object Detection Dataset for Autonomous Driving

Jianhua Han, Xiwen Liang, Hang Xu +8

Aiming at facilitating a real-world, ever-evolving and scalable autonomous driving system, we present a large-scale dataset for standardizing the evaluation of different self-super…

cs.CV2021133 cited

One Million Scenes for Autonomous Driving: ONCE Dataset

Jiageng Mao, Minzhe Niu, Chenhan Jiang +10

Current perception models in autonomous driving have become notorious for greatly relying on a mass of annotated data to cover unseen cases and address the long-tail problem. On th…

cs.CV20213 cited

Joint-DetNAS: Upgrade Your Detector with NAS, Pruning and Dynamic Distillation

Lewei Yao, Renjie Pi, Hang Xu +3

We propose Joint-DetNAS, a unified NAS framework for object detection, which integrates 3 key components: Neural Architecture Search, pruning, and Knowledge Distillation. Instead o…