activity
20172024
most citedBEVDet: High-performance Multi-camera 3D Object Detection in Bird-Eye-View

297 citations · 1.3k across the 37 of their papers we have counts for

collaborators

37 papers

cs.CV2024★ 5 cited

WorldDreamer: Towards General World Models for Video Generation via Predicting Masked Tokens

Xiaofeng Wang, Zheng Zhu, Guan Huang +3

World models play a crucial role in understanding and predicting the dynamics of the world, which is essential for video generation. However, existing world models are confined to…

cs.CV2023★ 15 cited

DriveDreamer: Towards Real-world-driven World Models for Autonomous Driving

Xiaofeng Wang, Zheng Zhu, Guan Huang +3

World models, especially in autonomous driving, are trending and drawing extensive attention due to their capacity for comprehending driving environments. The established world mod…

cs.CV2023★ 1 cited

CompletionFormer: Depth Completion with Convolutions and Vision Transformers

Zhang Youmin, Guo Xianda, Poggi Matteo +3

Given sparse depths and the corresponding RGB images, depth completion aims at spatially propagating the sparse measurements throughout the whole image to get a dense depth predict…

cs.CV2023★ 2 cited

Detachable Novel Views Synthesis of Dynamic Scenes Using Distribution-Driven Neural Radiance Fields

Boyu Zhang, Wenbo Xu, Zheng Zhu +1

Representing and synthesizing novel views in real-world dynamic scenes from casual monocular videos is a long-standing problem. Existing solutions typically approach dynamic scenes…

cs.CV2022★ 1 cited

Are We Ready for Vision-Centric Driving Streaming Perception? The ASAP Benchmark

Xiaofeng Wang, Zheng Zhu, Yunpeng Zhang +5

In recent years, vision-centric perception has flourished in various autonomous driving tasks, including 3D detection, semantic map construction, motion forecasting, and depth esti…

cs.CV2022★ 26 cited

BEVPoolv2: A Cutting-edge Implementation of BEVDet Toward Deployment

Junjie Huang, Guan Huang

We release a new codebase version of the BEVDet, dubbed branch dev2.0. With dev2.0, we propose BEVPoolv2 upgrade the view transformation process from the perspective of engineering…

cs.CV2022

A Simple Baseline for Multi-Camera 3D Object Detection

Yunpeng Zhang, Wenzhao Zheng, Zheng Zhu +3

3D object detection with surrounding cameras has been a promising direction for autonomous driving. In this paper, we present SimMOD, a Simple baseline for Multi-camera Object Dete…

cs.CV2022★ 3 cited

Crafting Monocular Cues and Velocity Guidance for Self-Supervised Multi-Frame Depth Learning

Xiaofeng Wang, Zheng Zhu, Guan Huang +4

Self-supervised monocular methods can efficiently learn depth information of weakly textured surfaces or reflective objects. However, the depth accuracy is limited due to the inher…

cs.CV2022★ 260 cited

MonoViT: Self-Supervised Monocular Depth Estimation with a Vision Transformer

Chaoqiang Zhao, Youmin Zhang, Matteo Poggi +6

Self-supervised monocular depth estimation is an attractive solution that does not require hard-to-source depth labels for training. Convolutional neural networks (CNNs) have recen…

cs.CV2022★ 84 cited

BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

Yunpeng Zhang, Zheng Zhu, Wenzhao Zheng +4

In this paper, we present BEVerse, a unified framework for 3D perception and prediction based on multi-camera systems. Unlike existing studies focusing on the improvement of single…

cs.CV2022★ 1 cited

Gait Recognition in the Wild: A Large-scale Benchmark and NAS-based Baseline

Xianda Guo, Zheng Zhu, Tian Yang +6

Gait benchmarks empower the research community to train and evaluate high-performance gait recognition systems. Even though growing efforts have been devoted to cross-view recognit…

cs.CV2022★ 1 cited

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…

cs.CV2022★ 10 cited

MVSTER: Epipolar Transformer for Efficient Multi-View Stereo

Xiaofeng Wang, Zheng Zhu, Fangbo Qin +5

Learning-based Multi-View Stereo (MVS) methods warp source images into the reference camera frustum to form 3D volumes, which are fused as a cost volume to be regularized by subseq…

cs.CV2022★ 10 cited

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…

cs.CV2022★ 17 cited

SurroundDepth: Entangling Surrounding Views for Self-Supervised Multi-Camera Depth Estimation

Yi Wei, Linqing Zhao, Wenzhao Zheng +5

Depth estimation from images serves as the fundamental step of 3D perception for autonomous driving and is an economical alternative to expensive depth sensors like LiDAR. The temp…

cs.CV2022★ 157 cited

BEVDet4D: Exploit Temporal Cues in Multi-camera 3D Object Detection

Junjie Huang, Guan Huang

Single frame data contains finite information which limits the performance of the existing vision-based multi-camera 3D object detection paradigms. For fundamentally pushing the pe…

cs.LG2021★ 91 cited

Joint Demand Prediction for Multimodal Systems: A Multi-task Multi-relational Spatiotemporal Graph Neural Network Approach

Yuebing Liang, Guan Huang, Zhan Zhao

Dynamic demand prediction is crucial for the efficient operation and management of urban transportation systems. Extensive research has been conducted on single-mode demand predict…

cs.CV2021★ 297 cited

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…

cs.CV2021★ 38 cited

DenseCLIP: Language-Guided Dense Prediction with Context-Aware Prompting

Yongming Rao, Wenliang Zhao, Guangyi Chen +5

Recent progress has shown that large-scale pre-training using contrastive image-text pairs can be a promising alternative for high-quality visual representation learning from natur…

cs.CV2021

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…

cs.CV2021★ 24 cited

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…

cs.CV2021

SIMPLE: SIngle-network with Mimicking and Point Learning for Bottom-up Human Pose Estimation

Jiabin Zhang, Zheng Zhu, Jiwen Lu +3

The practical application requests both accuracy and efficiency on multi-person pose estimation algorithms. But the high accuracy and fast inference speed are dominated by top-down…

cs.CV2021

Hippocampus-heuristic Character Recognition Network for Zero-shot Learning

Shaowei Wang, Guanjie Huang, Xiangyu Luo

The recognition of Chinese characters has always been a challenging task due to their huge variety and complex structures. The latest research proves that such an enormous characte…

cs.CV2021

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…