Publications

Non-uniform Timestep Sampling: Towards Faster Diffusion Model Training
Tianyi Zheng, Cong Geng, Peng-Tao Jiang, Ben Wan, Hao Zhang, Jinwei Chen, Jia Wang, and Bo Li
ACM Multimedia 2024.

Exploring bidirectional bounds for minimax-training of Energy-based models
Cong Geng, Jia Wang, Li Chen, Zhiyong Gao, Jes Frellsen, and Søren Hauberg
International Journal of Computer Vision (IJCV) (Major Revision).

Improving Adversarial Energy-Based Model via Diffusion Process
Cong Geng, Tian Han, Peng-Tao Jiang, Hao Zhang, Jinwei Chen, Søren Hauberg, and Bo Li
International Conference on Machine Learning (ICML) 2024.

Solving the Reconstruction-Generation Trade-Off: Generative Model with Implicit Embedding Learning
Cong Geng, Jia Wang, Li Chen, and Zhiyong Gao
Neurocomputing 2023.

Bounds all Around: Training Energy-based Models with Bidirectional Bounds
Cong Geng, Jia Wang, Zhiyong Gao, Jes Frellsen, and Søren Hauberg
Advances in Neural Information Processing Systems (NeurIPS) 2021.

Omni-GAN: On the Secrets of cGANs and Beyond
Peng Zhou, Lingxi Xie, Bingbing Ni, Cong Geng, and Qi Tian
IEEE International Conference on Computer Vision (ICCV) 2021.

Adversarial Text Image Super-Resolution Using Sinkhorn Distance
Cong Geng, Li Chen, Xiaoyun Zhang, and Zhiyong Gao
IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2020.

Wasserstein-Bounded Generative Adversarial Networks
Peng Zhou, Bingbing Ni, Lingxi Xie, Xiaopeng Zhang, Hang Wang, Cong Geng, and Qi Tian
Preprint 2020.

A Wavelet-based Learning for Face Hallucination with Loop Architecture
Cong Geng, Li Chen, Xiaoyun Zhang, Peng Zhou, and Zhiyong Gao
IEEE Visual Communications and Image Processing (VCIP) 2018.