Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN2.9k papers
- Centre National de la Recherche ScientifiqueFR2.7k papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT2.6k papers
- Institute of High Energy PhysicsCN2.6k papers
- University of Science and Technology of ChinaCN2.5k papers
- Peking UniversityCN2.4k papers
- University of Chinese Academy of SciencesCN2.3k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT2.3k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR2.3k papers
- Rutherford Appleton LaboratoryGB2.2k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT2.2k papers
- European Organization for Nuclear ResearchCH2.2k papers
110 papers · 2 filters
Adaptive Affinity for Associations in Multi-Target Multi-Camera Tracking
Yunzhong Hou, Zhongdao Wang, Shengjin Wang +1
Data associations in multi-target multi-camera tracking (MTMCT) usually estimate affinity directly from re-identification (re-ID) feature distances. However, we argue that it might…
Controllable Video Captioning with an Exemplar Sentence
Yitian Yuan, Lin Ma, Jingwen Wang +1
In this paper, we investigate a novel and challenging task, namely controllable video captioning with an exemplar sentence. Formally, given a video and a syntactically valid exempl…
Video Joint Modelling Based on Hierarchical Transformer for Co-summarization
Li Haopeng, Ke Qiuhong, Gong Mingming +1
Video summarization aims to automatically generate a summary (storyboard or video skim) of a video, which can facilitate large-scale video retrieval and browsing. Most of the exist…
NeRF-SR: High-Quality Neural Radiance Fields using Supersampling
Chen Wang, Xian Wu, Yuan-Chen Guo +3
We present NeRF-SR, a solution for high-resolution (HR) novel view synthesis with mostly low-resolution (LR) inputs. Our method is built upon Neural Radiance Fields (NeRF) that pre…
Graph Convolutional Module for Temporal Action Localization in Videos
Runhao Zeng, Wenbing Huang, Mingkui Tan +4
Temporal action localization has long been researched in computer vision. Existing state-of-the-art action localization methods divide each video into multiple action units (i.e.,…
Multiple Fusion Adaptation: A Strong Framework for Unsupervised Semantic Segmentation Adaptation
Kai Zhang, Yifan Sun, Rui Wang +2
This paper challenges the cross-domain semantic segmentation task, aiming to improve the segmentation accuracy on the unlabeled target domain without incurring additional annotatio…
Investigation of domain gap problem in several deep-learning-based CT metal artefact reduction methods
Muge Du, Kaichao Liang, Yinong Liu +1
Metal artefacts in CT images may disrupt image quality and interfere with diagnosis. Recently many deep-learning-based CT metal artefact reduction (MAR) methods have been proposed.…
ACR-Pose: Adversarial Canonical Representation Reconstruction Network for Category Level 6D Object Pose Estimation
Zhaoxin Fan, Zhengbo Song, Jian Xu +4
Recently, category-level 6D object pose estimation has achieved significant improvements with the development of reconstructing canonical 3D representations. However, the reconstru…
Attention Mechanisms in Computer Vision: A Survey
Meng-Hao Guo, Tian-Xing Xu, Jiang-Jiang Liu +7
Humans can naturally and effectively find salient regions in complex scenes. Motivated by this observation, attention mechanisms were introduced into computer vision with the aim o…
Sparse Steerable Convolutions: An Efficient Learning of SE(3)-Equivariant Features for Estimation and Tracking of Object Poses in 3D Space
Jiehong Lin, Hongyang Li, Ke Chen +2
As a basic component of SE(3)-equivariant deep feature learning, steerable convolution has recently demonstrated its advantages for 3D semantic analysis. The advantages are, howeve…
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
Zhengzhuo Xu, Zenghao Chai, Chun Yuan
Real-world data universally confronts a severe class-imbalance problem and exhibits a long-tailed distribution, i.e., most labels are associated with limited instances. The naïve m…
Self-supervised Feature-Gate Coupling for Dynamic Network Pruning
Mengnan Shi, Chang Liu, Jianbin Jiao +1
Gating modules have been widely explored in dynamic network pruning to reduce the run-time computational cost of deep neural networks while preserving the representation of feature…
Multiway Non-rigid Point Cloud Registration via Learned Functional Map Synchronization
Jiahui Huang, Tolga Birdal, Zan Gojcic +2
We present SyNoRiM, a novel way to jointly register multiple non-rigid shapes by synchronizing the maps relating learned functions defined on the point clouds. Even though the abil…
APANet: Adaptive Prototypes Alignment Network for Few-Shot Semantic Segmentation
Jiacheng Chen, Bin-Bin Gao, Zongqing Lu +3
Few-shot semantic segmentation aims to segment novel-class objects in a given query image with only a few labeled support images. Most advanced solutions exploit a metric learning…
KTNet: Knowledge Transfer for Unpaired 3D Shape Completion
Zhen Cao, Wenxiao Zhang, Xin Wen +4
Unpaired 3D object completion aims to predict a complete 3D shape from an incomplete input without knowing the correspondence between the complete and incomplete shapes. In this pa…
Focal and Global Knowledge Distillation for Detectors
Zhendong Yang, Zhe Li, Xiaohu Jiang +4
Knowledge distillation has been applied to image classification successfully. However, object detection is much more sophisticated and most knowledge distillation methods have fail…
Denoised Internal Models: a Brain-Inspired Autoencoder against Adversarial Attacks
Kaiyuan Liu, Xingyu Li, Yurui Lai +6
Despite its great success, deep learning severely suffers from robustness; that is, deep neural networks are very vulnerable to adversarial attacks, even the simplest ones. Inspire…
PatchCensor: Patch Robustness Certification for Transformers via Exhaustive Testing
Yuheng Huang, Lei Ma, Yuanchun Li
Vision Transformer (ViT) is known to be highly nonlinear like other classical neural networks and could be easily fooled by both natural and adversarial patch perturbations. This l…
Learning Modified Indicator Functions for Surface Reconstruction
Dong Xiao, Siyou Lin, Zuoqiang Shi +1
Surface reconstruction is a fundamental problem in 3D graphics. In this paper, we propose a learning-based approach for implicit surface reconstruction from raw point clouds withou…
Multi-Glimpse Network: A Robust and Efficient Classification Architecture based on Recurrent Downsampled Attention
Sia Huat Tan, Runpei Dong, Kaisheng Ma
Most feedforward convolutional neural networks spend roughly the same efforts for each pixel. Yet human visual recognition is an interaction between eye movements and spatial atten…
Imitating Arbitrary Talking Style for Realistic Audio-DrivenTalking Face Synthesis
Haozhe Wu, Jia Jia, Haoyu Wang +3
People talk with diversified styles. For one piece of speech, different talking styles exhibit significant differences in the facial and head pose movements. For example, the "exci…
ES-ImageNet: A Million Event-Stream Classification Dataset for Spiking Neural Networks
Yihan Lin, Wei Ding, Shaohua Qiang +2
With event-driven algorithms, especially the spiking neural networks (SNNs), achieving continuous improvement in neuromorphic vision processing, a more challenging event-stream-dat…
Detecting and Identifying Optical Signal Attacks on Autonomous Driving Systems
Jindi Zhang, Yifan Zhang, Kejie Lu +4
For autonomous driving, an essential task is to detect surrounding objects accurately. To this end, most existing systems use optical devices, including cameras and light detection…
MPSN: Motion-aware Pseudo Siamese Network for Indoor Video Head Detection in Buildings
Kailai Sun, Xiaoteng Ma, Peng Liu +1
Head detection in the indoor video is an essential component of building occupancy detection. While deep models have achieved remarkable progress in general object detection, they…