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20172026
most citedTopological Deep Learning: A Review of an Emerging Paradigm

58 citations · 89 across the 24 of their papers we have counts for

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18 papers · 1 filter

cs.CV2026

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…

cs.CV2026

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…

cs.CV2026

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…

cs.CV2025★ 2 cited

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…

cs.CV2025

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…

cs.CV2025★ 1 cited

StateSpace-SSL: Linear-Time Self-supervised Learning for Plant Disease Detection

Abdullah Al Mamun, Miaohua Zhang, David Ahmedt-Aristizabal +2

Self-supervised learning (SSL) is attractive for plant disease detection as it can exploit large collections of unlabeled leaf images, yet most existing SSL methods are built on CN…