2.4k citations · 2.9k across the 19 of their papers we have counts for
19 papers
Rethinking Lanes and Points in Complex Scenarios for Monocular 3D Lane Detection
Yifan Chang, Junjie Huang, Xiaofeng Wang +5
Monocular 3D lane detection is a fundamental task in autonomous driving. Although sparse-point methods lower computational load and maintain high accuracy in complex lane geometrie…
Detecting As Labeling: Rethinking LiDAR-camera Fusion in 3D Object Detection
Junjie Huang, Yun Ye, Zhujin Liang +2
3D object Detection with LiDAR-camera encounters overfitting in algorithm development which is derived from the violation of some fundamental rules. We refer to the data annotation…
OccFormer: Dual-path Transformer for Vision-based 3D Semantic Occupancy Prediction
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. Compared with the BEV p…
OpenOccupancy: A Large Scale Benchmark for Surrounding Semantic Occupancy Perception
Xiaofeng Wang, Zheng Zhu, Wenbo Xu +7
Semantic occupancy perception is essential for autonomous driving, as automated vehicles require a fine-grained perception of the 3D urban structures. However, existing relevant be…
Bridging Stereo Geometry and BEV Representation with Reliable Mutual Interaction for Semantic Scene Completion
Bohan Li, Yasheng Sun, Zhujin Liang +6
3D semantic scene completion (SSC) is an ill-posed perception task that requires inferring a dense 3D scene from limited observations. Previous camera-based methods struggle to pre…
WebFace260M: A Benchmark for Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
Face benchmarks empower the research community to train and evaluate high-performance face recognition systems. In this paper, we contribute a new million-scale recognition benchma…
HFT: Lifting Perspective Representations via Hybrid Feature Transformation
Jiayu Zou, Junrui Xiao, Zheng Zhu +4
Autonomous driving requires accurate and detailed Bird's Eye View (BEV) semantic segmentation for decision making, which is one of the most challenging tasks for high-level scene p…
BEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View
Junjie Huang, Guan Huang, Zheng Zhu +2
Autonomous driving perceives its surroundings for decision making, which is one of the most complex scenarios in visual perception. The success of paradigm innovation in solving th…
Face-NMS: A Core-set Selection Approach for Efficient Face Recognition
Yunze Chen, Junjie Huang, Jiagang Zhu +4
Recently, face recognition in the wild has achieved remarkable success and one key engine is the increasing size of training data. For example, the largest face dataset, WebFace42M…
Masked Face Recognition Challenge: The WebFace260M Track Report
Zheng Zhu, Guan Huang, Jiankang Deng +9
According to WHO statistics, there are more than 204,617,027 confirmed COVID-19 cases including 4,323,247 deaths worldwide till August 12, 2021. During the coronavirus epidemic, al…
Structure-Aware Face Clustering on a Large-Scale Graph with Nodes
Shuai Shen, Wanhua Li, Zheng Zhu +4
Face clustering is a promising method for annotating unlabeled face images. Recent supervised approaches have boosted the face clustering accuracy greatly, however their performanc…
WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition
Zheng Zhu, Guan Huang, Jiankang Deng +8
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 da…
AID: Pushing the Performance Boundary of Human Pose Estimation with Information Dropping Augmentation
Junjie Huang, Zheng Zhu, Guan Huang +1
Both appearance cue and constraint cue are vital for human pose estimation. However, there is a tendency in most existing works to overfitting the former and overlook the latter. I…
High Performance Visual Object Tracking with Unified Convolutional Networks
Zheng Zhu, Wei Zou, Guan Huang +2
Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks. Nonetheless, the chosen CNN features are always pre-trained in…
EANet: Enhancing Alignment for Cross-Domain Person Re-identification
Houjing Huang, Wenjie Yang, Xiaotang Chen +5
Person re-identification (ReID) has achieved significant improvement under the single-domain setting. However, directly exploiting a model to new domains is always faced with huge…
Action Machine: Rethinking Action Recognition in Trimmed Videos
Jiagang Zhu, Wei Zou, Liang Xu +6
Existing methods in video action recognition mostly do not distinguish human body from the environment and easily overfit the scenes and objects. In this work, we present a concept…
Attention-guided Unified Network for Panoptic Segmentation
Yanwei Li, Xinze Chen, Zheng Zhu +4
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…
UCT: Learning Unified Convolutional Networks for Real-time Visual Tracking
Zheng Zhu, Guan Huang, Wei Zou +2
Convolutional neural networks (CNN) based tracking approaches have shown favorable performance in recent benchmarks. Nonetheless, the chosen CNN features are always pre-trained in…
Conditional Random Fields as Recurrent Neural Networks
Shuai Zheng, Sadeep Jayasumana, Bernardino Romera-Paredes +5
Pixel-level labelling tasks, such as semantic segmentation, play a central role in image understanding. Recent approaches have attempted to harness the capabilities of deep learnin…