91 citations · 193 across the 13 of their papers we have counts for
8 papers · 1 filter
A Simple Single-Scale Vision Transformer for Object Localization and Instance Segmentation
Wuyang Chen, Xianzhi Du, Fan Yang +8
This work presents a simple vision transformer design as a strong baseline for object localization and instance segmentation tasks. Transformers recently demonstrate competitive pe…
Font Completion and Manipulation by Cycling Between Multi-Modality Representations
Ye Yuan, Wuyang Chen, Zhaowen Wang +4
Generating font glyphs of consistent style from one or a few reference glyphs, i.e., font completion, is an important task in topographical design. As the problem is more well-defi…
Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics
Wuyang Chen, Xinyu Gong, Junru Wu +5
This work targets designing a principled and unified training-free framework for Neural Architecture Search (NAS), with high performance, low cost, and in-depth interpretation. NAS…
DANCE: DAta-Network Co-optimization for Efficient Segmentation Model Training and Inference
Chaojian Li, Wuyang Chen, Yuchen Gu +4
Semantic segmentation for scene understanding is nowadays widely demanded, raising significant challenges for the algorithm efficiency, especially its applications on resource-limi…
Contrastive Syn-to-Real Generalization
Wuyang Chen, Zhiding Yu, Shalini De Mello +4
Training on synthetic data can be beneficial for label or data-scarce scenarios. However, synthetically trained models often suffer from poor generalization in real domains due to…
Neural Architecture Search on ImageNet in Four GPU Hours: A Theoretically Inspired Perspective
Wuyang Chen, Xinyu Gong, Zhangyang Wang
Neural Architecture Search (NAS) has been explosively studied to automate the discovery of top-performer neural networks. Current works require heavy training of supernet or intens…
Learning to Optimize: A Primer and A Benchmark
Tianlong Chen, Xiaohan Chen, Wuyang Chen +4
Learning to optimize (L2O) is an emerging approach that leverages machine learning to develop optimization methods, aiming at reducing the laborious iterations of hand engineering.…
Sandwich Batch Normalization: A Drop-In Replacement for Feature Distribution Heterogeneity
Xinyu Gong, Wuyang Chen, Tianlong Chen +1
We present Sandwich Batch Normalization (SaBN), a frustratingly easy improvement of Batch Normalization (BN) with only a few lines of code changes. SaBN is motivated by addressing…