13 papers
Probing Diffusion Denoising Dynamics for Contrastive Representation Learning
Yasong Dai, Zeeshan Hayder, David Ahmedt-Aristizabal +1
Text-to-image diffusion models exhibit unprecedented generative capability and contain rich intermediate representations that can be useful for discriminative vision tasks. Motivat…
BiFM: Bidirectional Flow Matching for Few-Step Image Editing and Generation
Yasong Dai, Zeeshan Hayder, David Ahmedt-Aristizabal +1
Recent diffusion and flow matching models have demonstrated strong capabilities in image generation and editing by progressively removing noise through iterative sampling. While th…
ARMFlow: AutoRegressive MeanFlow for Online 3D Human Reaction Generation
Zichen Geng, Zeeshan Hayder, Wei Liu +2
3D human reaction generation faces three main challenges:(1) high motion fidelity, (2) real-time inference, and (3) autoregressive adaptability for online scenarios. Existing metho…
Disentangled Hierarchical VAE for 3D Human-Human Interaction Generation
Zichen Geng, Zeeshan Hayder, Bo Miao +3
Generating realistic 3D Human-Human Interaction (HHI) requires coherent modeling of the physical plausibility of the agents and their interaction semantics. Existing methods compre…
PSMamba: Progressive Self-supervised Vision Mamba for Plant Disease Recognition
Abdullah Al Mamun, Miaohua Zhang, David Ahmedt-Aristizabal +2
Self-supervised Learning (SSL) has become a powerful paradigm for representation learning without manual annotations. However, most existing frameworks focus on global alignment an…
Quality-Driven and Diversity-Aware Sample Expansion for Robust Marine Obstacle Segmentation
Miaohua Zhang, Mohammad Ali Armin, Xuesong Li +5
Marine obstacle detection demands robust segmentation under challenging conditions, such as sun glitter, fog, and rapidly changing wave patterns. These factors degrade image qualit…