3.2k citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Beihang UniversityCN29 papers
- Peng Cheng LaboratoryCN4 papers
- Chinese Academy of SciencesCN3 papers
- Peking UniversityCN3 papers
- Baidu (China)CN2 papers
- Institute of Information EngineeringCN2 papers
- National University of Defense TechnologyCN2 papers
- Shanghai Jiao Tong UniversityCN2 papers
- Tencent (China)CN2 papers
- Tsinghua UniversityCN2 papers
- Advanced Digital Sciences CenterSG1 paper
- Agency for Science, Technology and ResearchSG1 paper
19 papers · 1 filter
GSV3D: Gaussian Splatting-based Geometric Distillation with Stable Video Diffusion for Single-Image 3D Object Generation
Ye Tao, Jiawei Zhang, Yahao Shi +2
Image-based 3D generation has vast applications in robotics and gaming, where high-quality, diverse outputs and consistent 3D representations are crucial. However, existing methods…
Learning Fine-Grained Segmentation of 3D Shapes without Part Labels
Xiaogang Wang, Xun Sun, Xinyu Cao +2
Learning-based 3D shape segmentation is usually formulated as a semantic labeling problem, assuming that all parts of training shapes are annotated with a given set of tags. This a…
PIE-NET: Parametric Inference of Point Cloud Edges
Xiaogang Wang, Yuelang Xu, Kai Xu +4
We introduce an end-to-end learnable technique to robustly identify feature edges in 3D point cloud data. We represent these edges as a collection of parametric curves (i.e.,lines,…
Counting dense objects in remote sensing images
Guangshuai Gao, Qingjie Liu, Yunhong Wang
Estimating accurate number of interested objects from a given image is a challenging yet important task. Significant efforts have been made to address this problem and achieve grea…
A Novel and Efficient Tumor Detection Framework for Pancreatic Cancer via CT Images
Zhengdong Zhang, Shuai Li, Ziyang Wang +1
As Deep Convolutional Neural Networks (DCNNs) have shown robust performance and results in medical image analysis, a number of deep-learning-based tumor detection methods were deve…
Gated Path Selection Network for Semantic Segmentation
Qichuan Geng, Hong Zhang, Xiaojuan Qi +3
Semantic segmentation is a challenging task that needs to handle large scale variations, deformations and different viewpoints. In this paper, we develop a novel network named Gate…
Salient Object Detection with Purificatory Mechanism and Structural Similarity Loss
Jia Li, Jinming Su, Changqun Xia +2
By the aid of attention mechanisms to weight the image features adaptively, recent advanced deep learning-based models encourage the predicted results to approximate the ground-tru…
A Sparse Representation Based Joint Demosaicing Method for Single-Chip Polarized Color Sensor
Sijia Wen, Yinqiang Zheng, Feng Lu
The emergence of the single-chip polarized color sensor now allows for simultaneously capturing chromatic and polarimetric information of the scene on a monochromatic image plane.…
Distortion-adaptive Salient Object Detection in 360 Omnidirectional Images
Jia Li, Jinming Su, Changqun Xia +1
Image-based salient object detection (SOD) has been extensively explored in the past decades. However, SOD on 360 omnidirectional images is less studied owing to the lack o…
Understanding Adversarial Attacks on Deep Learning Based Medical Image Analysis Systems
Xingjun Ma, Yuhao Niu, Lin Gu +4
Deep neural networks (DNNs) have become popular for medical image analysis tasks like cancer diagnosis and lesion detection. However, a recent study demonstrates that medical deep…
Spatiotemporal Knowledge Distillation for Efficient Estimation of Aerial Video Saliency
Jia Li, Kui Fu, Shengwei Zhao +1
The performance of video saliency estimation techniques has achieved significant advances along with the rapid development of Convolutional Neural Networks (CNNs). However, devices…
Ultrafast Video Attention Prediction with Coupled Knowledge Distillation
Kui Fu, Peipei Shi, Yafei Song +3
Large convolutional neural network models have recently demonstrated impressive performance on video attention prediction. Conventionally, these models are with intensive computati…
Learning from Large-scale Noisy Web Data with Ubiquitous Reweighting for Image Classification
Jia Li, Yafei Song, Jianfeng Zhu +5
Many advances of deep learning techniques originate from the efforts of addressing the image classification task on large-scale datasets. However, the construction of such clean da…
Detail Preserving Depth Estimation from a Single Image Using Attention Guided Networks
Zhixiang Hao, Yu Li, Shaodi You +1
Convolutional Neural Networks have demonstrated superior performance on single image depth estimation in recent years. These works usually use stacked spatial pooling or strided co…
VoxSegNet: Volumetric CNNs for Semantic Part Segmentation of 3D Shapes
Zongji Wang, Feng Lu
Voxel is an important format to represent geometric data, which has been widely used for 3D deep learning in shape analysis due to its generalization ability and regular data forma…
Road Extraction by Deep Residual U-Net
Zhengxin Zhang, Qingjie Liu, Yunhong Wang
Road extraction from aerial images has been a hot research topic in the field of remote sensing image analysis. In this letter, a semantic segmentation neural network which combine…
Too Far to See? Not Really! --- Pedestrian Detection with Scale-aware Localization Policy
Xiaowei Zhang, Li Cheng, Bo Li +1
A major bottleneck of pedestrian detection lies on the sharp performance deterioration in the presence of small-size pedestrians that are relatively far from the camera. Motivated…
A Benchmark Dataset and Saliency-guided Stacked Autoencoders for Video-based Salient Object Detection
Jia Li, Changqun Xia, Xiaowu Chen
Image-based salient object detection (SOD) has been extensively studied in the past decades. However, video-based SOD is much less explored since there lack large-scale video datas…
Salient Object Detection: A Survey
Ali Borji, Ming-Ming Cheng, Qibin Hou +2
Detecting and segmenting salient objects from natural scenes, often referred to as salient object detection, has attracted great interest in computer vision. While many models have…