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20202026
most citedFine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained Features

1 citations · 3 across the 5 of their papers we have counts for

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cs.CV2026

Recolour What Matters: Region-Aware Colour Editing via Token-Level Diffusion

Yuqi Yang, Dongliang Chang, Yijia Ling +2

Colour is one of the most perceptually salient yet least controllable attributes in image generation. Although recent diffusion models can modify object colours from user instructi…

cs.CV2023

DemoFusion: Democratising High-Resolution Image Generation With No $$$

Ruoyi Du, Dongliang Chang, Timothy Hospedales +2

High-resolution image generation with Generative Artificial Intelligence (GenAI) has immense potential but, due to the enormous capital investment required for training, it is incr…

cs.CV20211 cited

Fine-Grained Visual Classification via Simultaneously Learning of Multi-regional Multi-grained Features

Dongliang Chang, Yixiao Zheng, Zhanyu Ma +2

Fine-grained visual classification is a challenging task that recognizes the sub-classes belonging to the same meta-class. Large inter-class similarity and intra-class variance is…

cs.CV20201 cited

Knowledge Transfer Based Fine-grained Visual Classification

Siqing Zhang, Ruoyi Du, Dongliang Chang +2

Fine-grained visual classification (FGVC) aims to distinguish the sub-classes of the same category and its essential solution is to mine the subtle and discriminative regions. Conv…

cs.CV2020

Fine-Grained Visual Classification via Progressive Multi-Granularity Training of Jigsaw Patches

Ruoyi Du, Dongliang Chang, Ayan Kumar Bhunia +4

Fine-grained visual classification (FGVC) is much more challenging than traditional classification tasks due to the inherently subtle intra-class object variations. Recent works ma…