activity
20242026
most citedEvaluation of Text-to-Video Generation Models: A Dynamics Perspective

3 citations · 5 across the 15 of their papers we have counts for

collaborators

18 papers

cs.CV2026

ReCALL: Recalibrating Capability Degradation for MLLM-based Composed Image Retrieval

Tianyu Yang, Chenwei He, Xiangzhao Hao +6

Composed Image Retrieval (CIR) aims to retrieve target images based on a hybrid query comprising a reference image and a modification text. Early dual-tower Vision-Language Models…

cs.CV2026

LightMover: Generative Light Movement with Color and Intensity Controls

Gengze Zhou, Tianyu Wang, Soo Ye Kim +7

We present LightMover, a framework for controllable light manipulation in single images that leverages video diffusion priors to produce physically plausible illumination changes w…

cs.CV2026

WISER: Wider Search, Deeper Thinking, and Adaptive Fusion for Training-Free Zero-Shot Composed Image Retrieval

Tianyue Wang, Leigang Qu, Tianyu Yang +4

Zero-Shot Composed Image Retrieval (ZS-CIR) aims to retrieve target images given a multimodal query (comprising a reference image and a modification text), without training on anno…

cs.CV2026

Language-Conditioned World Modeling for Visual Navigation

Yifei Dong, Fengyi Wu, Yilong Dai +11

Goal-conditioned visual navigation has been a long-standing testbed for embodied AI. We study a natural language-conditioned variant, language-conditioned visual navigation (LCVN),…

cs.CV2026

RetouchIQ: MLLM Agents for Instruction-Based Image Retouching with Generalist Reward

Qiucheng Wu, Jing Shi, Simon Jenni +4

Recent advances in multimodal large language models (MLLMs) have shown great potential for extending vision-language reasoning to professional tool-based image editing, enabling in…

cs.CV2026

RL-RIG: A Generative Spatial Reasoner via Intrinsic Reflection

Tianyu Wang, Zhiyuan Ma, Qian Wang +3

Recent advancements in image generation have achieved impressive results in producing high-quality images. However, existing image generation models still generally struggle with a…

cs.GR2026

Statistical Blendshape Calculation and Analysis for Graphics Applications

Shuxian Li, Tianyue Wang, Chris Twombly

With the development of virtualization and AI, real-time facial avatar animation is widely used in entertainment, office, business and other fields. Against this background, blends…

cs.CV2025

Self-Evaluation Unlocks Any-Step Text-to-Image Generation

Xin Yu, Xiaojuan Qi, Zhengqi Li +6

We introduce the Self-Evaluating Model (Self-E), a novel, from-scratch training approach for text-to-image generation that supports any-step inference. Self-E learns from data simi…

cs.LG2025

Conformal Correction for Efficiency May be at Odds with Entropy

Senrong Xu, Tianyu Wang, Zenan Li +4

Conformal prediction (CP) provides a comprehensive framework to produce statistically rigorous uncertainty sets for black-box machine learning models. To further improve the effici…

cs.CV2025

EditVerse: Unifying Image and Video Editing and Generation with In-Context Learning

Xuan Ju, Tianyu Wang, Yuqian Zhou +11

Recent advances in foundation models highlight a clear trend toward unification and scaling, showing emergent capabilities across diverse domains. While image generation and editin…

cs.CV2025

Are VLMs Ready for Lane Topology Awareness in Autonomous Driving?

Xin Chen, Jia He, Maozheng Li +5

Vision-Language Models (VLMs) have recently shown remarkable progress in multimodal reasoning, yet their applications in autonomous driving remain limited. In particular, the abili…

cs.CV2025

OmniVCus: Feedforward Subject-driven Video Customization with Multimodal Control Conditions

Yuanhao Cai, He Zhang, Xi Chen +11

Existing feedforward subject-driven video customization methods mainly study single-subject scenarios due to the difficulty of constructing multi-subject training data pairs. Anoth…

cs.CV2025

Enhancing Text-to-Image Diffusion Transformer via Split-Text Conditioning

Yu Zhang, Jialei Zhou, Xinchen Li +6

Current text-to-image diffusion generation typically employs complete-text conditioning. Due to the intricate syntax, diffusion transformers (DiTs) inherently suffer from a compreh…

cs.CV2025

3D-LLaVA: Towards Generalist 3D LMMs with Omni Superpoint Transformer

Jiajun Deng, Tianyu He, Li Jiang +3

Current 3D Large Multimodal Models (3D LMMs) have shown tremendous potential in 3D-vision-based dialogue and reasoning. However, how to further enhance 3D LMMs to achieve fine-grai…

cs.CV2024★ 1 cited

Generative Video Propagation

Shaoteng Liu, Tianyu Wang, Jui-Hsien Wang +8

Large-scale video generation models have the inherent ability to realistically model natural scenes. In this paper, we demonstrate that through a careful design of a generative vid…

cs.CV2024

MetaShadow: Object-Centered Shadow Detection, Removal, and Synthesis

Tianyu Wang, Jianming Zhang, Haitian Zheng +7

Shadows are often under-considered or even ignored in image editing applications, limiting the realism of the edited results. In this paper, we introduce MetaShadow, a three-in-one…

cs.CV2024★ 3 cited

Evaluation of Text-to-Video Generation Models: A Dynamics Perspective

Mingxiang Liao, Hannan Lu, Xinyu Zhang +6

Comprehensive and constructive evaluation protocols play an important role in the development of sophisticated text-to-video (T2V) generation models. Existing evaluation protocols…

cs.HC2024★ 1 cited

Personalized Interiors at Scale: Leveraging AI for Efficient and Customizable Design Solutions

Kaiwen Zhou, Tianyu Wang

In this paper, we introduce an innovative application of artificial intelligence in the realm of interior design through the integration of Stable Diffusion and Dreambooth models.…