activity
20172022
most citedDynamicViT: Efficient Vision Transformers with Dynamic Token Sparsification

311 citations · 1k across the 54 of their papers we have counts for

collaborators

66 papers

cs.CV2022

Token-Label Alignment for Vision Transformers

Han Xiao, Wenzhao Zheng, Zheng Zhu +2

Data mixing strategies (e.g., CutMix) have shown the ability to greatly improve the performance of convolutional neural networks (CNNs). They mix two images as inputs for training…

cs.CV20221 cited

OPERA: Omni-Supervised Representation Learning with Hierarchical Supervisions

Chengkun Wang, Wenzhao Zheng, Zheng Zhu +2

The pretrain-finetune paradigm in modern computer vision facilitates the success of self-supervised learning, which tends to achieve better transferability than supervised learning…

cs.RO2022

Planning Irregular Object Packing via Hierarchical Reinforcement Learning

Sichao Huang, Ziwei Wang, Jie Zhou +1

Object packing by autonomous robots is an im-portant challenge in warehouses and logistics industry. Most conventional data-driven packing planning approaches focus on regular cubo…

cs.CV20221 cited

Probabilistic Deep Metric Learning for Hyperspectral Image Classification

Chengkun Wang, Wenzhao Zheng, Xian Sun +2

This paper proposes a probabilistic deep metric learning (PDML) framework for hyperspectral image classification, which aims to predict the category of each pixel for an image capt…

cs.CV2022

SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation

Ziyi Wang, Yongming Rao, Xumin Yu +2

Conventional point cloud semantic segmentation methods usually employ an encoder-decoder architecture, where mid-level features are locally aggregated to extract geometric informat…

cs.CV202284 cited

BEVerse: Unified Perception and Prediction in Birds-Eye-View for Vision-Centric Autonomous Driving

Yunpeng Zhang, Zheng Zhu, Wenzhao Zheng +4

In this paper, we present BEVerse, a unified framework for 3D perception and prediction based on multi-camera systems. Unlike existing studies focusing on the improvement of single…