Sheng Cheng

I'm a PhD student at ASU. I'm working with Yezhou Yang, and co-advised by Yi Ren. I closely collaborate with Maitreya Patel, Changhoon Kim. Previously, I received my M.Eng. in Electrical Engineering from University of Illinois at Urbana-Champaign, working with Ruoyu Sun, and received B.S. from Huazhong University of Science and Technology.

Email  /  CV  /  Scholar  /  Twitter  /  Github  /  Linkedin


I'm interested in computer vision and machine learning. My focus lies in the domain of vision & language (particularly in Text-to-Image generation) and domain generalization & robustness.

Revising Text-to-Image Prior for Improved Text Conditioned Image Generations
Maitreya Patel, Changhoon Kim, Sheng Cheng, Chitta Baral, Yezhou Yang
CVPR, 2024
project page / demo / arXiv / code / media coverage (Twitter of AK, MarkTechPost, MultiPlatformAI, Video discussion, Paper Digest)

Improving the Parameter and Data Efficiency of the Text-to-Image Priors for UnCLIP Family Models with contrastive loss.

WOUAF: Weight Modulation for User Attribution and Fingerprinting in Text-to-Image Diffusion Models
Changhoon Kim, Kyle Min, Maitreya Patel, Sheng Cheng, Yezhou Yang
CVPR, 2024
project page / demo / arXiv

Enabling the Integration of up to 32-bit (~4 billion) fingerprints into Text-to-Image Diffusion Models without loss in image quality.

Self-supervised Learning to Discover Physical Objects and Predict Their Interactions from Raw Videos
Sheng Cheng, Yezhou Yang, Yang Jiao, Yi Ren
NeurIPS AI4Science workshop, 2023

Jointly learning to discover physical objects and predict their dynamics in the videos for physical environment.

Adversarial Bayesian Augmentation for Single-Source Domain Generalization
Sheng Cheng, Tejas Gokhale, Yezhou Yang
ICCV, 2023
arXiv / code

Adversarial Learning + Bayesian neural network for single-source domain generalization.

SSR-GNNs: Stroke-based Sketch Representation with Graph Neural Networks
Sheng Cheng, Yi Ren, Yezhou Yang
CVPR Sketch workshop, 2022
arXiv / code

Transformation invariant sketch recognition by decomposing to strokes and composing by graph neural network.

Data-Driven Learning of Three-Point Correlation Functions as Microstructure Representations
Sheng Cheng, Yang Jiao, Yi Ren
Acta Materialia, 2022
arXiv / code

Learning the microstructure representation by 3-point correlation functions.

Evaluating the Robustness of Bayesian Neural Networks Against Different Types of Attacks
Yutian Pang, Sheng Cheng, Jueming Hu, Yongming Liu,
CVPR Adversarial Machine Learning workshop, 2021

Evaluating the robustness gain of Bayesian neural networks on image classification tasks.

Work Experience

Amazon Alexa, 2023 Summer
  • Zero-shot mask annotation free open-vocabulary semantic segmentation by the text-to-image model.

  •, 2022 Summer
  • a real-time system evaluating and scoring the human exercises by cameras.

  • Hikvision Research, 2019 Spring
  • Research on a new metric for super-resolution based on one-to-many mapping nature.
  • Service & Honor

    Reviewer: CVPR 2024; CVPR 2022, 2023 workshop
    2023-24 ASU Graduate College Travel Award

    This website template is taken from source code.