13 citations · 35 across the 7 of their papers we have counts for
4 papers · 2 filters
Demystify Transformers & Convolutions in Modern Image Deep Networks
Xiaowei Hu, Min Shi, Weiyun Wang +9
Vision transformers have gained popularity recently, leading to the development of new vision backbones with improved features and consistent performance gains. However, these adva…
Design What You Desire: Icon Generation from Orthogonal Application and Theme Labels
Yinpeng Chen, Zhiyu Pan, Min Shi +3
Generative adversarial networks (GANs) have been trained to be professional artists able to create stunning artworks such as face generation and image style transfer. In this paper…
3D Instances as 1D Kernels
Yizheng Wu, Min Shi, Shuaiyuan Du +3
We introduce a 3D instance representation, termed instance kernels, where instances are represented by one-dimensional vectors that encode the semantic, positional, and shape infor…
Represent, Compare, and Learn: A Similarity-Aware Framework for Class-Agnostic Counting
Min Shi, Hao Lu, Chen Feng +2
Class-agnostic counting (CAC) aims to count all instances in a query image given few exemplars. A standard pipeline is to extract visual features from exemplars and match them with…