1 code implementation • 28 Feb 2024 • Chaokang Jiang, Guangming Wang, Jiuming Liu, Hesheng Wang, Zhuang Ma, Zhenqiang Liu, Zhujin Liang, Yi Shan, Dalong Du
We present a novel approach from the perspective of auto-labelling, aiming to generate a large number of 3D scene flow pseudo labels for real-world LiDAR point clouds.
1 code implementation • 29 Nov 2023 • Jiuming Liu, Guangming Wang, Weicai Ye, Chaokang Jiang, Jinru Han, Zhe Liu, Guofeng Zhang, Dalong Du, Hesheng Wang
Furthermore, we also develop an uncertainty estimation module within diffusion to evaluate the reliability of estimated scene flow.
1 code implementation • 13 Nov 2023 • JunJie Huang, Yun Ye, Zhujin Liang, Yi Shan, Dalong Du
3D object Detection with LiDAR-camera encounters overfitting in algorithm development which is derived from the violation of some fundamental rules.
1 code implementation • 17 Oct 2023 • Hao Lu, Yunpeng Zhang, Qing Lian, Dalong Du, Yingcong Chen
In our approach, we render diverse view maps from BEV features and rectify the perspective bias of these maps, leveraging implicit foreground volumes to bridge the camera and BEV planes.
1 code implementation • ICCV 2023 • Yunpeng Zhang, Zheng Zhu, Dalong Du
The vision-based perception for autonomous driving has undergone a transformation from the bird-eye-view (BEV) representations to the 3D semantic occupancy.
3D Semantic Occupancy Prediction 3D Semantic Scene Completion from a single RGB image +3
1 code implementation • 24 Mar 2023 • Bohan Li, Yasheng Sun, Zhujin Liang, Dalong Du, Zhuanghui Zhang, XiaoFeng Wang, Yunnan Wang, Xin Jin, Wenjun Zeng
3D semantic scene completion (SSC) is an ill-posed perception task that requires inferring a dense 3D scene from limited observations.
1 code implementation • ICCV 2023 • XiaoFeng Wang, Zheng Zhu, Wenbo Xu, Yunpeng Zhang, Yi Wei, Xu Chi, Yun Ye, Dalong Du, Jiwen Lu, Xingang Wang
Towards a comprehensive benchmarking of surrounding perception algorithms, we propose OpenOccupancy, which is the first surrounding semantic occupancy perception benchmark.
no code implementations • 21 Apr 2022 • Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Dalong Du, Jiwen Lu, Jie zhou
For a comprehensive evaluation of face matchers, three recognition tasks are performed under standard, masked and unbiased settings, respectively.
1 code implementation • 11 Apr 2022 • Jiayu Zou, Junrui Xiao, Zheng Zhu, JunJie Huang, Guan Huang, Dalong Du, Xingang Wang
In order to reap the benefits and avoid the drawbacks of CBFT and CFFT, we propose a novel framework with a Hybrid Feature Transformation module (HFT).
no code implementations • CVPR 2022 • Yunpeng Zhang, Wenzhao Zheng, Zheng Zhu, Guan Huang, Dalong Du, Jie zhou, Jiwen Lu
In this paper, we propose a general method to learn appropriate embeddings for dimension estimation in monocular 3D object detection.
2 code implementations • 22 Dec 2021 • JunJie Huang, Guan Huang, Zheng Zhu, Yun Ye, Dalong Du
As a fast version, BEVDet-Tiny scores 31. 2% mAP and 39. 2% NDS on the nuScenes val set.
Ranked #20 on Robust Camera Only 3D Object Detection on nuScenes-C
no code implementations • 10 Sep 2021 • Yunze Chen, JunJie Huang, Jiagang Zhu, Zheng Zhu, Tian Yang, Guan Huang, Dalong Du
The current research on this problem mainly focuses on designing an efficient Fully-connected layer (FC) to reduce GPU memory consumption caused by a large number of identities.
no code implementations • 16 Aug 2021 • Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jia Guo, Jiwen Lu, Dalong Du, Jie zhou
There are second phase of the challenge till October 1, 2021 and on-going leaderboard.
1 code implementation • CVPR 2021 • Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou
To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.
1 code implementation • 24 Mar 2021 • Shuai Shen, Wanhua Li, Zheng Zhu, Guan Huang, Dalong Du, Jiwen Lu, Jie zhou
To address the dilemma of large-scale training and efficient inference, we propose the STructure-AwaRe Face Clustering (STAR-FC) method.
no code implementations • CVPR 2021 • Zheng Zhu, Guan Huang, Jiankang Deng, Yun Ye, JunJie Huang, Xinze Chen, Jiagang Zhu, Tian Yang, Jiwen Lu, Dalong Du, Jie zhou
In this paper, we contribute a new million-scale face benchmark containing noisy 4M identities/260M faces (WebFace260M) and cleaned 2M identities/42M faces (WebFace42M) training data, as well as an elaborately designed time-constrained evaluation protocol.
Ranked #1 on Face Verification on IJB-C (training dataset metric)
2 code implementations • 17 Aug 2020 • Junjie Huang, Zheng Zhu, Guan Huang, Dalong Du
As AID successfully pushes the performance boundary of human pose estimation problem by considerable margin and sets a new state-of-the-art, we hope AID to be a regular configuration for training human pose estimators.
Ranked #1 on Multi-Person Pose Estimation on COCO minival
3 code implementations • CVPR 2020 • Junjie Huang, Zheng Zhu, Feng Guo, Guan Huang, Dalong Du
Specifically, by investigating the standard data processing in state-of-the-art approaches mainly including coordinate system transformation and keypoint format transformation (i. e., encoding and decoding), we find that the results obtained by common flipping strategy are unaligned with the original ones in inference.
Ranked #15 on Pose Estimation on COCO test-dev
no code implementations • 26 Aug 2019 • Zheng Zhu, Wei Zou, Guan Huang, Dalong Du, Chang Huang
In this paper, we propose an end-to-end framework to learn the convolutional features and perform the tracking process simultaneously, namely, a unified convolutional tracker (UCT).
3 code implementations • 29 Dec 2018 • Houjing Huang, Wenjie Yang, Xiaotang Chen, Xin Zhao, Kaiqi Huang, Jinbin Lin, Guan Huang, Dalong Du
Person re-identification (ReID) has achieved significant improvement under the single-domain setting.
no code implementations • 14 Dec 2018 • Jiagang Zhu, Wei Zou, Liang Xu, Yiming Hu, Zheng Zhu, Manyu Chang, Jun-Jie Huang, Guan Huang, Dalong Du
On NTU RGB-D, Action Machine achieves the state-of-the-art performance with top-1 accuracies of 97. 2% and 94. 3% on cross-view and cross-subject respectively.
Ranked #1 on Action Recognition on UTD-MHAD
no code implementations • CVPR 2019 • Yanwei Li, Xinze Chen, Zheng Zhu, Lingxi Xie, Guan Huang, Dalong Du, Xingang Wang
This paper studies panoptic segmentation, a recently proposed task which segments foreground (FG) objects at the instance level as well as background (BG) contents at the semantic level.
Ranked #24 on Panoptic Segmentation on COCO test-dev
no code implementations • 10 Nov 2017 • Zheng Zhu, Guan Huang, Wei Zou, Dalong Du, Chang Huang
Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks.
6 code implementations • ICCV 2015 • Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes, Vibhav Vineet, Zhizhong Su, Dalong Du, Chang Huang, Philip H. S. Torr
Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding.
Ranked #36 on Semantic Segmentation on PASCAL VOC 2012 test