Ming Gui

According to our database, Ming Gui authored at least 18 papers between 2020 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2026

Denoising, Fast and Slow: Difficulty-Aware Adaptive Sampling for Image Generation.

Johannes Schusterbauer, Ming Gui, Yusong Li, Pingchuan Ma, Felix Krause, Björn Ommer

CoRR, April, 2026

Guiding Token-Sparse Diffusion Models.

Felix Krause, Stefan Andreas Baumann, Johannes Schusterbauer, Olga Grebenkova, Ming Gui, Vincent Tao Hu, Björn Ommer

CoRR, January, 2026

2025

DisMo: Disentangled Motion Representations for Open-World Motion Transfer.

Thomas Ressler-Antal, Frank Fundel, Malek Ben Alaya, Stefan Andreas Baumann, Felix Krause, Ming Gui, Björn Ommer

CoRR, November, 2025

Adapting Self-Supervised Representations as a Latent Space for Efficient Generation.

Ming Gui, Johannes Schusterbauer, Timy Phan, Felix Krause, Josh M. Susskind, Miguel Ángel Bautista, Björn Ommer

CoRR, October, 2025

SCFlow: Implicitly Learning Style and Content Disentanglement with Flow Models.

Pingchuan Ma, Xiaopei Yang, Yusong Li, Ming Gui, Felix Krause, Johannes Schusterbauer, Björn Ommer

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Stochastic Interpolants for Revealing Stylistic Flows Across the History of Art.

Pingchuan Ma, Ming Gui, Johannes Schusterbauer, Xiaopei Yang, Olga Grebenkova, Vincent Tao Hu, Björn Ommer

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Tread: Token Routing for Efficient Architecture-Agnostic Diffusion Training.

Felix Krause, Timy Phan, Ming Gui, Stefan Andreas Baumann, Vincent Tao Hu, Björn Ommer

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2025

Diff2Flow: Training Flow Matching Models via Diffusion Model Alignment.

Johannes Schusterbauer, Ming Gui, Frank Fundel, Björn Ommer

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

DepthFM: Fast Generative Monocular Depth Estimation with Flow Matching.

Ming Gui, Johannes Schusterbauer, Ulrich Prestel, Pingchuan Ma, Dmytro Kotovenko, Olga Grebenkova, Stefan Andreas Baumann, Vincent Tao Hu, Björn Ommer

Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, 2025

2024

Diffusion Models and Representation Learning: A Survey.

Michael Fuest, Pingchuan Ma, Ming Gui, Johannes S. Fischer, Vincent Tao Hu, Björn Ommer

CoRR, 2024

DepthFM: Fast Monocular Depth Estimation with Flow Matching.

Ming Gui, Johannes S. Fischer, Ulrich Prestel, Pingchuan Ma, Dmytro Kotovenko, Olga Grebenkova, Stefan Andreas Baumann, Vincent Tao Hu, Björn Ommer

CoRR, 2024

FMBoost: Boosting Latent Diffusion with Flow Matching.

Johannes Schusterbauer, Ming Gui, Pingchuan Ma, Nick Stracke, Stefan Andreas Baumann, Vincent Tao Hu, Björn Ommer

Proceedings of the Computer Vision - ECCV 2024, 2024

ZigMa: A DiT-style Zigzag Mamba Diffusion Model.

Vincent Tao Hu, Stefan Andreas Baumann, Ming Gui, Olga Grebenkova, Pingchuan Ma, Johannes S. Fischer, Björn Ommer

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

Boosting Latent Diffusion with Flow Matching.

Johannes S. Fischer, Ming Gui, Pingchuan Ma, Nick Stracke, Stefan Andreas Baumann, Björn Ommer

CoRR, 2023

2022

SVIT: Hybrid Vision Transformer Models with Scattering Transform.

Tianming Qiu, Ming Gui, Cheng Yan, Ziqing Zhao, Hao Shen

Proceedings of the 32nd IEEE International Workshop on Machine Learning for Signal Processing, 2022

Laplace Approximation for Real-Time Uncertainty Estimation in Object Detection.

Ming Gui, Tianming Qiu, Fridolin Bauer, Hao Shen

Proceedings of the 25th IEEE International Conference on Intelligent Transportation Systems, 2022

Block-based Novel Haptic Data Reduction for Time-delayed Teleoperation.

Ming Gui, Xiao Xu, Eckehard G. Steinbach

Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems, 2022

2020

Adaptive Packet Rate Control for the Mitigation of Bursty Haptic Traffic in Teleoperation Systems.

Ming Gui, Xiao Xu, Eckehard G. Steinbach

Proceedings of the 2020 IEEE Haptics Symposium, 2020