83 citations · 188 across the 23 of their papers we have counts for
15 papers · 1 filter
Rotation-Constrained Cross-View Feature Fusion for Multi-View Appearance-based Gaze Estimation
Yoichiro Hisadome, Tianyi Wu, Jiawei Qin +1
Appearance-based gaze estimation has been actively studied in recent years. However, its generalization performance for unseen head poses is still a significant limitation for exis…
Learning Video-independent Eye Contact Segmentation from In-the-Wild Videos
Tianyi Wu, Yusuke Sugano
Human eye contact is a form of non-verbal communication and can have a great influence on social behavior. Since the location and size of the eye contact targets vary across differ…
Adaptive Sparse ViT: Towards Learnable Adaptive Token Pruning by Fully Exploiting Self-Attention
Xiangcheng Liu, Tianyi Wu, Guodong Guo
Vision transformer has emerged as a new paradigm in computer vision, showing excellent performance while accompanied by expensive computational cost. Image token pruning is one of…
Region-level Contrastive and Consistency Learning for Semi-Supervised Semantic Segmentation
Jianrong Zhang, Tianyi Wu, Chuanghao Ding +2
Current semi-supervised semantic segmentation methods mainly focus on designing pixel-level consistency and contrastive regularization. However, pixel-level regularization is sensi…
CATrans: Context and Affinity Transformer for Few-Shot Segmentation
Shan Zhang, Tianyi Wu, Sitong Wu +1
Few-shot segmentation (FSS) aims to segment novel categories given scarce annotated support images. The crux of FSS is how to aggregate dense correlations between support and query…
Feature Selective Transformer for Semantic Image Segmentation
Fangjian Lin, Tianyi Wu, Sitong Wu +2
Recently, it has attracted more and more attentions to fuse multi-scale features for semantic image segmentation. Various works were proposed to employ progressive local or global…
Dynamic Group Transformer: A General Vision Transformer Backbone with Dynamic Group Attention
Kai Liu, Tianyi Wu, Cong Liu +1
Recently, Transformers have shown promising performance in various vision tasks. To reduce the quadratic computation complexity caused by each query attending to all keys/values, v…
Pale Transformer: A General Vision Transformer Backbone with Pale-Shaped Attention
Sitong Wu, Tianyi Wu, Haoru Tan +1
Recently, Transformers have shown promising performance in various vision tasks. To reduce the quadratic computation complexity caused by the global self-attention, various methods…
3D Reconstruction from public webcams
Tianyu Wu, Konrad Schindler, Cenek Albl
We investigate the possibility of 3D scene reconstruction from two or more overlapping webcam streams. A large, and growing, number of webcams observe places of interest and are pu…
Ice Monitoring in Swiss Lakes from Optical Satellites and Webcams using Machine Learning
Manu Tom, Rajanie Prabha, Tianyu Wu +3
Continuous observation of climate indicators, such as trends in lake freezing, is important to understand the dynamics of the local and global climate system. Consequently, lake ic…
GINet: Graph Interaction Network for Scene Parsing
Tianyi Wu, Yu Lu, Yu Zhu +4
Recently, context reasoning using image regions beyond local convolution has shown great potential for scene parsing. In this work, we explore how to incorporate the linguistic kno…
Consensus Feature Network for Scene Parsing
Tianyi Wu, Sheng Tang, Rui Zhang +2
Scene parsing is challenging as it aims to assign one of the semantic categories to each pixel in scene images. Thus, pixel-level features are desired for scene parsing. However, c…
UGAN: Untraceable GAN for Multi-Domain Face Translation
Defa Zhu, Si Liu, Wentao Jiang +4
The multi-domain image-to-image translation is a challenging task where the goal is to translate an image into multiple different domains. The target-only characteristics are desir…
Tree-structured Kronecker Convolutional Network for Semantic Segmentation
Tianyi Wu, Sheng Tang, Rui Zhang +2
Most existing semantic segmentation methods employ atrous convolution to enlarge the receptive field of filters, but neglect partial information. To tackle this issue, we firstly p…
CGNet: A Light-weight Context Guided Network for Semantic Segmentation
Tianyi Wu, Sheng Tang, Rui Zhang +1
The demand of applying semantic segmentation model on mobile devices has been increasing rapidly. Current state-of-the-art networks have enormous amount of parameters hence unsuita…