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cs.CV2026

OmniShow: Unifying Multimodal Conditions for Human-Object Interaction Video Generation

Donghao Zhou, Guisheng Liu, Hao Yang +9

In this work, we study Human-Object Interaction Video Generation (HOIVG), which aims to synthesize high-quality human-object interaction videos conditioned on text, reference image…

cs.CV2026

TAMISeg: Text-Aligned Multi-scale Medical Image Segmentation with Semantic Encoder Distillation

Qiang Gao, Yi Wang, Yong Zhang +4

Medical image segmentation remains challenging due to limited fine-grained annotations, complex anatomical structures, and image degradation from noise, low contrast, or illuminati…

cs.CV2025

Consistent and Controllable Image Animation with Motion Linear Diffusion Transformers

Xin Ma, Yaohui Wang, Genyun Jia +3

Image animation has seen significant progress, driven by the powerful generative capabilities of diffusion models. However, maintaining appearance consistency with static input ima…

cs.CV2025

Training-free Stylized Text-to-Image Generation with Fast Inference

Xin Ma, Yaohui Wang, Xinyuan Chen +2

Although diffusion models exhibit impressive generative capabilities, existing methods for stylized image generation based on these models often require textual inversion or fine-t…

cs.CV2024

Cinemo: Consistent and Controllable Image Animation with Motion Diffusion Models

Xin Ma, Yaohui Wang, Gengyun Jia +4

Diffusion models have achieved great progress in image animation due to powerful generative capabilities. However, maintaining spatio-temporal consistency with detailed information…

cs.CV2024

Latte: Latent Diffusion Transformer for Video Generation

Xin Ma, Yaohui Wang, Xinyuan Chen +5

We propose Latte, a novel Latent Diffusion Transformer for video generation. Latte first extracts spatio-temporal tokens from input videos and then adopts a series of Transformer b…