activity
20162022
most citedProgressive Differentiable Architecture Search: Bridging the Depth Gap between Search and Evaluation

133 citations · 651 across the 50 of their papers we have counts for

collaborators

82 papers

physics.ao-ph2022127 cited

Pangu-Weather: A 3D High-Resolution Model for Fast and Accurate Global Weather Forecast

Kaifeng Bi, Lingxi Xie, Hengheng Zhang +3

In this paper, we present Pangu-Weather, a deep learning based system for fast and accurate global weather forecast. For this purpose, we establish a data-driven environment by dow…

cs.CV2022

Learnable Distribution Calibration for Few-Shot Class-Incremental Learning

Binghao Liu, Boyu Yang, Lingxi Xie +3

Few-shot class-incremental learning (FSCIL) faces challenges of memorizing old class distributions and estimating new class distributions given few training samples. In this study,…

cs.CV202212 cited

HiViT: Hierarchical Vision Transformer Meets Masked Image Modeling

Xiaosong Zhang, Yunjie Tian, Wei Huang +4

Recently, masked image modeling (MIM) has offered a new methodology of self-supervised pre-training of vision transformers. A key idea of efficient implementation is to discard the…

cs.CV2022

Domain-Agnostic Prior for Transfer Semantic Segmentation

Xinyue Huo, Lingxi Xie, Hengtong Hu +3

Unsupervised domain adaptation (UDA) is an important topic in the computer vision community. The key difficulty lies in defining a common property between the source and target dom…

cs.CV20223 cited

CenterNet++ for Object Detection

Kaiwen Duan, Song Bai, Lingxi Xie +3

There are two mainstreams for object detection: top-down and bottom-up. The state-of-the-art approaches mostly belong to the first category. In this paper, we demonstrate that the…

cs.CV20221 cited

Beyond Masking: Demystifying Token-Based Pre-Training for Vision Transformers

Yunjie Tian, Lingxi Xie, Jiemin Fang +6

The past year has witnessed a rapid development of masked image modeling (MIM). MIM is mostly built upon the vision transformers, which suggests that self-supervised visual represe…