4 papers · 1 filter
IC-Effect: Precise and Efficient Video Effects Editing via In-Context Learning
Yuanhang Li, Yiren Song, Junzhe Bai +4
We propose \textbf{IC-Effect}, an instruction-guided, DiT-based framework for few-shot video VFX editing that synthesizes complex effects (\eg flames, particles and cartoon charact…
Generative Neural Video Compression via Video Diffusion Prior
Qi Mao, Hao Cheng, Tinghan Yang +2
We present GNVC-VD, the first DiT-based generative neural video compression framework built upon an advanced video generation foundation model, where spatio-temporal latent compres…
EmoAgent: A Multi-Agent Framework for Diverse Affective Image Manipulation
Qi Mao, Haobo Hu, Yujie He +3
Affective Image Manipulation (AIM) aims to alter visual elements within an image to evoke specific emotional responses from viewers. However, existing AIM approaches rely on rigid…
StarVid: Enhancing Semantic Alignment in Video Diffusion Models via Spatial and SynTactic Guided Attention Refocusing
Yuanhang Li, Qi Mao, Lan Chen +5
Recent advances in text-to-video (T2V) generation with diffusion models have garnered significant attention. However, they typically perform well in scenes with a single object and…