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Haoyang Huang

6 papers indexed

arxivcs.CV2026-07-23

Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On

Yong Liu, Xiaolong Fu, Zihang Xu, Wen Xue, Xueheng Li, Lin Song, et al.

We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is fashion-native, built for try-on through a dedicated data engine and try-on-specific training. Given one or more reference item…

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arxivcs.CV2026-07-23

HalluScope: Fine-grained Hallucination Diagnosis for Multimodal Large Language Models

Weilin Jin, Mingyu Wang, Wenbo Li, Haoyang Huang, Yifan Wu, Ying Li, et al.

Although Multimodal Large Language Models have achieved strong performance across a wide range of vision-language tasks, they still suffer from hallucinations, where model outputs become inconsistent with the visual content, textual context, or commonsense knowledge. Existing stu…

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arxivcs.CV2026-07-23

Geo3R: Mitigating Spatial Reasoning Hallucination in Multimodal Large Language Models

Mingyu Wang, Weilin Jin, Wenbo Li, Haoyang Huang, Tong Jia, Ying Li

Despite remarkable progress in visual understanding, Multimodal Large Language Models (MLLMs) remain prone to hallucinations when reasoning about spatial relationships, often producing judgments that contradict the true 3D structure of the scene. Though several existing works hav…

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arxivcs.CV2026-07-22

Self Gradient Forcing: Native Long Video Extrapolation

Junhao Zhuang, Shiyi Zhang, Yuxuan Bian, Yaowei Li, Yawen Luo, Yijun Liu, et al.

Recent autoregressive video diffusion methods are increasingly built upon Self Forcing, where the student is trained on histories produced by its own rollout rather than ground-truth video contexts. This reduces exposure bias, but the historical key-value cache is still used by f…

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arxivcs.CV2026-07-03

Perceptual Flow Matching for Few-Step Generative Modeling

Chuyang Zhao, Yifei Song, Hongfa Wang, Jianlong Yuan, Yuan Zhang, Siming Fu, et al.

We propose Perceptual Flow Matching (PFM), a simple yet effective framework for few-step generation in flow-matching models. Rather than performing velocity regression in the conventional VAE latent space, PFM supervises flow matching in a perceptual feature space using pretraine…

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