40 citations · 76 across the 18 of their papers we have counts for
18 papers
ControLRM: Fast and Controllable 3D Generation via Large Reconstruction Model
Hongbin Xu, Weitao Chen, Zhipeng Zhou +4
Despite recent advancements in 3D generation methods, achieving controllability still remains a challenging issue. Current approaches utilizing score-distillation sampling are hind…
CostFormer:Cost Transformer for Cost Aggregation in Multi-view Stereo
Weitao Chen, Hongbin Xu, Zhipeng Zhou +4
The core of Multi-view Stereo(MVS) is the matching process among reference and source pixels. Cost aggregation plays a significant role in this process, while previous methods focu…
Semi-supervised Deep Multi-view Stereo
Hongbin Xu, Weitao Chen, Yang Liu +5
Significant progress has been witnessed in learning-based Multi-view Stereo (MVS) under supervised and unsupervised settings. To combine their respective merits in accuracy and com…
Rethinking the Zigzag Flattening for Image Reading
Qingsong Zhao, Yi Wang, Zhipeng Zhou +4
Sequence ordering of word vector matters a lot to text reading, which has been proven in natural language processing (NLP). However, the rule of different sequence ordering in comp…
CP-Net: Contour-Perturbed Reconstruction Network for Self-Supervised Point Cloud Learning
Mingye Xu, Yali Wang, Zhipeng Zhou +2
Self-supervised learning has not been fully explored for point cloud analysis. Current frameworks are mainly based on point cloud reconstruction. Given only 3D coordinates, such ap…
Learning Dynamical Human-Joint Affinity for 3D Pose Estimation in Videos
Junhao Zhang, Yali Wang, Zhipeng Zhou +3
Graph Convolution Network (GCN) has been successfully used for 3D human pose estimation in videos. However, it is often built on the fixed human-joint affinity, according to human…
Digging into Uncertainty in Self-supervised Multi-view Stereo
Hongbin Xu, Zhipeng Zhou, Yali Wang +4
Self-supervised Multi-view stereo (MVS) with a pretext task of image reconstruction has achieved significant progress recently. However, previous methods are built upon intuitions,…
Scaled ReLU Matters for Training Vision Transformers
Pichao Wang, Xue Wang, Hao Luo +5
Vision transformers (ViTs) have been an alternative design paradigm to convolutional neural networks (CNNs). However, the training of ViTs is much harder than CNNs, as it is sensit…
An Efficient Training Approach for Very Large Scale Face Recognition
Kai Wang, Shuo Wang, Panpan Zhang +7
Face recognition has achieved significant progress in deep learning era due to the ultra-large-scale and welllabeled datasets. However, training on the outsize datasets is time-con…
When to Fold'em: How to answer Unanswerable questions
Marshall Ho, Zhipeng Zhou, Judith He
We present 3 different question-answering models trained on the SQuAD2.0 dataset -- BIDAF, DocumentQA and ALBERT Retro-Reader -- demonstrating the improvement of language models in…
Self-supervised Multi-view Stereo via Effective Co-Segmentation and Data-Augmentation
Hongbin Xu, Zhipeng Zhou, Yu Qiao +2
Recent studies have witnessed that self-supervised methods based on view synthesis obtain clear progress on multi-view stereo (MVS). However, existing methods rely on the assumptio…
Practical Two-party Privacy-preserving Neural Network Based on Secret Sharing
Zhengqiang Ge, Zhipeng Zhou, Dong Guo +1
Neural networks, with the capability to provide efficient predictive models, have been widely used in medical, financial, and other fields, bringing great convenience to our lives.…
PC-HMR: Pose Calibration for 3D Human Mesh Recovery from 2D Images/Videos
Tianyu Luan, Yali Wang, Junhao Zhang +3
The end-to-end Human Mesh Recovery (HMR) approach has been successfully used for 3D body reconstruction. However, most HMR-based frameworks reconstruct human body by directly learn…
MogFace: Towards a Deeper Appreciation on Face Detection
Yang Liu, Fei Wang, Jiankang Deng +3
Benefiting from the pioneering design of generic object detectors, significant achievements have been made in the field of face detection. Typically, the architectures of the backb…
Investigate Indistinguishable Points in Semantic Segmentation of 3D Point Cloud
Mingye Xu, Zhipeng Zhou, Junhao Zhang +1
This paper investigates the indistinguishable points (difficult to predict label) in semantic segmentation for large-scale 3D point clouds. The indistinguishable points consist of…
Learning Geometry-Disentangled Representation for Complementary Understanding of 3D Object Point Cloud
Mutian Xu, Junhao Zhang, Zhipeng Zhou +3
In 2D image processing, some attempts decompose images into high and low frequency components for describing edge and smooth parts respectively. Similarly, the contour and flat are…
SmallBigNet: Integrating Core and Contextual Views for Video Classification
Xianhang Li, Yali Wang, Zhipeng Zhou +1
Temporal convolution has been widely used for video classification. However, it is performed on spatio-temporal contexts in a limited view, which often weakens its capacity of lear…
Geometry Sharing Network for 3D Point Cloud Classification and Segmentation
Mingye Xu, Zhipeng Zhou, Yu Qiao
In spite of the recent progresses on classifying 3D point cloud with deep CNNs, large geometric transformations like rotation and translation remain challenging problem and harm th…