most citedFitDiT: Advancing the Authentic Garment Details for High-fidelity Virtual Try-on

1 citations · 1 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV2025

OracleAgent: A Multimodal Reasoning Agent for Oracle Bone Script Research

Caoshuo Li, Zengmao Ding, Xiaobin Hu +13

As one of the earliest writing systems, Oracle Bone Script (OBS) preserves the cultural and intellectual heritage of ancient civilizations. However, current OBS research faces two…

cs.CV2025

Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models

Yuansen Liu, Haiming Tang, Jinlong Peng +12

Multimodal Large Language Models (MLLMs) have demonstrated significant advances in visual understanding tasks. However, their capacity to comprehend human-centric scenes has rarely…

cs.CV2025

StrandDesigner: Towards Practical Strand Generation with Sketch Guidance

Na Zhang, Moran Li, Chengming Xu +6

Realistic hair strand generation is crucial for applications like computer graphics and virtual reality. While diffusion models can generate hairstyles from text or images, these i…

cs.CV2025

OracleFusion: Assisting the Decipherment of Oracle Bone Script with Structurally Constrained Semantic Typography

Caoshuo Li, Zengmao Ding, Xiaobin Hu +10

As one of the earliest ancient languages, Oracle Bone Script (OBS) encapsulates the cultural records and intellectual expressions of ancient civilizations. Despite the discovery of…

cs.CV2025

VTBench: Comprehensive Benchmark Suite Towards Real-World Virtual Try-on Models

Hu Xiaobin, Liang Yujie, Luo Donghao +5

While virtual try-on has achieved significant progress, evaluating these models towards real-world scenarios remains a challenge. A comprehensive benchmark is essential for three k…

cs.CV2025

When Preferences Diverge: Aligning Diffusion Models with Minority-Aware Adaptive DPO

Lingfan Zhang, Chen Liu, Chengming Xu +5

In recent years, the field of image generation has witnessed significant advancements, particularly in fine-tuning methods that align models with universal human preferences. This…