83 citations · 188 across the 23 of their papers we have counts for
10 papers · 1 filter
Learning biological neuronal networks with artificial neural networks: neural oscillations
Ruilin Zhang, Zhongyi Wang, Tianyi Wu +4
First-principles-based modelings have been extremely successful in providing crucial insights and predictions for complex biological functions and phenomena. However, they can be h…
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…
Multi-band oscillations emerge from a simple spiking network
Tianyi Wu, Yuhang Cai, Ruilin Zhang +3
In the brain, coherent neuronal activities often appear simultaneously in multiple frequency bands, e.g., as combinations of alpha (8-12 Hz), beta (12.5-30 Hz), gamma (30-120 Hz) o…
IGN : Implicit Generative Networks
Haozheng Luo, Tianyi Wu, Colin Feiyu Han +1
In this work, we build recent advances in distributional reinforcement learning to give a state-of-art distributional variant of the model based on the IQN. We achieve this by usin…
Deeply Supervised Skin Lesions Diagnosis with Stage and Branch Attention
Wei Dai, Rui Liu, Tianyi Wu +3
Accurate and unbiased examinations of skin lesions are critical for the early diagnosis and treatment of skin diseases. Visual features of skin lesions vary significantly because t…
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…