480 citations · 2.2k across the 106 of their papers we have counts for
107 papers
Pose-Free Neural Radiance Fields via Implicit Pose Regularization
Jiahui Zhang, Fangneng Zhan, Yingchen Yu +5
Pose-free neural radiance fields (NeRF) aim to train NeRF with unposed multi-view images and it has achieved very impressive success in recent years. Most existing works share the…
WaveNeRF: Wavelet-based Generalizable Neural Radiance Fields
Muyu Xu, Fangneng Zhan, Jiahui Zhang +5
Neural Radiance Field (NeRF) has shown impressive performance in novel view synthesis via implicit scene representation. However, it usually suffers from poor scalability as requir…
One-Shot Action Recognition via Multi-Scale Spatial-Temporal Skeleton Matching
Siyuan Yang, Jun Liu, Shijian Lu +2
One-shot skeleton action recognition, which aims to learn a skeleton action recognition model with a single training sample, has attracted increasing interest due to the challenge…
Online Map Vectorization for Autonomous Driving: A Rasterization Perspective
Gongjie Zhang, Jiahao Lin, Shuang Wu +5
Vectorized high-definition (HD) map is essential for autonomous driving, providing detailed and precise environmental information for advanced perception and planning. However, cur…
A Survey of Label-Efficient Deep Learning for 3D Point Clouds
Aoran Xiao, Xiaoqin Zhang, Ling Shao +1
In the past decade, deep neural networks have achieved significant progress in point cloud learning. However, collecting large-scale precisely-annotated training data is extremely…
Weakly Supervised 3D Open-vocabulary Segmentation
Kunhao Liu, Fangneng Zhan, Jiahui Zhang +6
Open-vocabulary segmentation of 3D scenes is a fundamental function of human perception and thus a crucial objective in computer vision research. However, this task is heavily impe…
Audio-Driven Talking Face Generation with Diverse yet Realistic Facial Animations
Rongliang Wu, Yingchen Yu, Fangneng Zhan +3
Audio-driven talking face generation, which aims to synthesize talking faces with realistic facial animations (including accurate lip movements, vivid facial expression details and…
POCE: Pose-Controllable Expression Editing
Rongliang Wu, Yingchen Yu, Fangneng Zhan +3
Facial expression editing has attracted increasing attention with the advance of deep neural networks in recent years. However, most existing methods suffer from compromised editin…
Face Transformer: Towards High Fidelity and Accurate Face Swapping
Kaiwen Cui, Rongliang Wu, Fangneng Zhan +1
Face swapping aims to generate swapped images that fuse the identity of source faces and the attributes of target faces. Most existing works address this challenging task through 3…
3D Semantic Segmentation in the Wild: Learning Generalized Models for Adverse-Condition Point Clouds
Aoran Xiao, Jiaxing Huang, Weihao Xuan +6
Robust point cloud parsing under all-weather conditions is crucial to level-5 autonomy in autonomous driving. However, how to learn a universal 3D semantic segmentation (3DSS) mode…
Self-Supervised 3D Action Representation Learning with Skeleton Cloud Colorization
Siyuan Yang, Jun Liu, Shijian Lu +3
3D Skeleton-based human action recognition has attracted increasing attention in recent years. Most of the existing work focuses on supervised learning which requires a large numbe…
Vision-Language Models for Vision Tasks: A Survey
Jingyi Zhang, Jiaxing Huang, Sheng Jin +1
Most visual recognition studies rely heavily on crowd-labelled data in deep neural networks (DNNs) training, and they usually train a DNN for each single visual recognition task, l…
StyleRF: Zero-shot 3D Style Transfer of Neural Radiance Fields
Kunhao Liu, Fangneng Zhan, Yiwen Chen +5
3D style transfer aims to render stylized novel views of a 3D scene with multi-view consistency. However, most existing work suffers from a three-way dilemma over accurate geometry…
Modeling Continuous Motion for 3D Point Cloud Object Tracking
Zhipeng Luo, Gongjie Zhang, Changqing Zhou +4
The task of 3D single object tracking (SOT) with LiDAR point clouds is crucial for various applications, such as autonomous driving and robotics. However, existing approaches have…
Regularized Vector Quantization for Tokenized Image Synthesis
Jiahui Zhang, Fangneng Zhan, Christian Theobalt +1
Quantizing images into discrete representations has been a fundamental problem in unified generative modeling. Predominant approaches learn the discrete representation either in a…
Backdoor Attacks Against Deep Image Compression via Adaptive Frequency Trigger
Yi Yu, Yufei Wang, Wenhan Yang +3
Recent deep-learning-based compression methods have achieved superior performance compared with traditional approaches. However, deep learning models have proven to be vulnerable t…
DETR4D: Direct Multi-View 3D Object Detection with Sparse Attention
Zhipeng Luo, Changqing Zhou, Gongjie Zhang +1
3D object detection with surround-view images is an essential task for autonomous driving. In this work, we propose DETR4D, a Transformer-based framework that explores sparse atten…
Domain Adaptive Scene Text Detection via Subcategorization
Zichen Tian, Chuhui Xue, Jingyi Zhang +1
Most existing scene text detectors require large-scale training data which cannot scale well due to two major factors: 1) scene text images often have domain-specific distributions…
Exploring Point-BEV Fusion for 3D Point Cloud Object Tracking with Transformer
Zhipeng Luo, Changqing Zhou, Liang Pan +6
With the prevalence of LiDAR sensors in autonomous driving, 3D object tracking has received increasing attention. In a point cloud sequence, 3D object tracking aims to predict the…
TransPillars: Coarse-to-Fine Aggregation for Multi-Frame 3D Object Detection
Zhipeng Luo, Gongjie Zhang, Changqing Zhou +3
3D object detection using point clouds has attracted increasing attention due to its wide applications in autonomous driving and robotics. However, most existing studies focus on s…
Latent Multi-Relation Reasoning for GAN-Prior based Image Super-Resolution
Jiahui Zhang, Fangneng Zhan, Yingchen Yu +3
Recently, single image super-resolution (SR) under large scaling factors has witnessed impressive progress by introducing pre-trained generative adversarial networks (GANs) as prio…
Towards Efficient Use of Multi-Scale Features in Transformer-Based Object Detectors
Gongjie Zhang, Zhipeng Luo, Zichen Tian +3
Multi-scale features have been proven highly effective for object detection but often come with huge and even prohibitive extra computation costs, especially for the recent Transfo…
PolarMix: A General Data Augmentation Technique for LiDAR Point Clouds
Aoran Xiao, Jiaxing Huang, Dayan Guan +3
LiDAR point clouds, which are usually scanned by rotating LiDAR sensors continuously, capture precise geometry of the surrounding environment and are crucial to many autonomous det…
Meta-DETR: Image-Level Few-Shot Detection with Inter-Class Correlation Exploitation
Gongjie Zhang, Zhipeng Luo, Kaiwen Cui +2
Few-shot object detection has been extensively investigated by incorporating meta-learning into region-based detection frameworks. Despite its success, the said paradigm is still c…