213 citations · 410 across the 9 of their papers we have counts for
16 papers
MiniViT: Compressing Vision Transformers with Weight Multiplexing
Jinnian Zhang, Houwen Peng, Kan Wu +4
Vision Transformer (ViT) models have recently drawn much attention in computer vision due to their high model capability. However, ViT models suffer from huge number of parameters,…
Learning to Track Objects from Unlabeled Videos
Jilai Zheng, Chao Ma, Houwen Peng +1
In this paper, we propose to learn an Unsupervised Single Object Tracker (USOT) from scratch. We identify that three major challenges, i.e., moving object discovery, rich temporal…
Rethinking and Improving Relative Position Encoding for Vision Transformer
Kan Wu, Houwen Peng, Minghao Chen +2
Relative position encoding (RPE) is important for transformer to capture sequence ordering of input tokens. General efficacy has been proven in natural language processing. However…
AutoFormer: Searching Transformers for Visual Recognition
Minghao Chen, Houwen Peng, Jianlong Fu +1
Recently, pure transformer-based models have shown great potentials for vision tasks such as image classification and detection. However, the design of transformer networks is chal…
Probing Inter-modality: Visual Parsing with Self-Attention for Vision-Language Pre-training
Hongwei Xue, Yupan Huang, Bei Liu +4
Vision-Language Pre-training (VLP) aims to learn multi-modal representations from image-text pairs and serves for downstream vision-language tasks in a fine-tuning fashion. The dom…
LightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Bin Yan, Houwen Peng, Kan Wu +3
Object tracking has achieved significant progress over the past few years. However, state-of-the-art trackers become increasingly heavy and expensive, which limits their deployment…