5 citations · 6 across the 14 of their papers we have counts for
15 papers
Mise-en-Video: Fine-Grained 3D Control for Multi-Shot Video Generation
Yingshuang Zou, Xiaoyu Shi, Yawen Luo +8
Recent advances in text-to-video generation have enabled high-fidelity single-shot synthesis, yet practical storytelling creation requires multi-shot videos with both strong inter-…
EasyVFX: Frequency-Driven Decoupling for Resource-Efficient VFX Generation
Yue Ma, Xu Ye, Qinghe Wang +9
Generating high-fidelity visual effects (VFX) typically demands massive datasets and prohibitive computational power due to the intricate coupling of spatial textures and temporal…
Video2LoRA: Unified Semantic-Controlled Video Generation via Per-Reference-Video LoRA
Zexi Wu, Baolu Li, Jing Dai +5
Achieving semantic alignment across diverse video generation conditions remains a significant challenge. Methods that rely on explicit structural guidance often enforce rigid spati…
Group Editing: Edit Multiple Images in One Go
Yue Ma, Xinyu Wang, Qianli Ma +9
In this paper, we tackle the problem of performing consistent and unified modifications across a set of related images. This task is particularly challenging because these images m…
Know3D: Prompting 3D Generation with Knowledge from Vision-Language Models
Wenyue Chen, Wenjue Chen, Peng Li +6
Recent advances in 3D generation have improved the fidelity and geometric details of synthesized 3D assets. However, due to the inherent ambiguity of single-view observations and t…
SemanticGen: Video Generation in Semantic Space
Jianhong Bai, Xiaoshi Wu, Xintao Wang +9
State-of-the-art video generative models typically learn the distribution of video latents in the VAE space and map them to pixels using a VAE decoder. While this approach can gene…
MultiShotMaster: A Controllable Multi-Shot Video Generation Framework
Qinghe Wang, Xiaoyu Shi, Baolu Li +7
Current video generation techniques excel at single-shot clips but struggle to produce narrative multi-shot videos, which require flexible shot arrangement, coherent narrative, and…
RelightMaster: Precise Video Relighting with Multi-plane Light Images
Weikang Bian, Xiaoyu Shi, Zhaoyang Huang +6
Recent advances in diffusion models enable high-quality video generation and editing, but precise relighting with consistent video contents, which is critical for shaping scene atm…
VFXMaster: Unlocking Dynamic Visual Effect Generation via In-Context Learning
Baolu Li, Yiming Zhang, Qinghe Wang +8
Visual effects (VFX) are crucial to the expressive power of digital media, yet their creation remains a major challenge for generative AI. Prevailing methods often rely on the one-…
Layout-Conditioned Autoregressive Text-to-Image Generation via Structured Masking
Zirui Zheng, Takashi Isobe, Tong Shen +12
Although autoregressive (AR) models have demonstrated remarkable success in image generation, extending these models to layout-conditioned generation remains challenging due to the…
CineMaster: A 3D-Aware and Controllable Framework for Cinematic Text-to-Video Generation
Qinghe Wang, Yawen Luo, Xiaoyu Shi +7
In this work, we present CineMaster, a novel framework for 3D-aware and controllable text-to-video generation. Our goal is to empower users with comparable controllability as profe…
MoTrans: Customized Motion Transfer with Text-driven Video Diffusion Models
Xiaomin Li, Xu Jia, Qinghe Wang +5
Existing pretrained text-to-video (T2V) models have demonstrated impressive abilities in generating realistic videos with basic motion or camera movement. However, these models exh…
CharacterFactory: Sampling Consistent Characters with GANs for Diffusion Models
Qinghe Wang, Baolu Li, Xiaomin Li +4
Recent advances in text-to-image models have opened new frontiers in human-centric generation. However, these models cannot be directly employed to generate images with consistent…
StableIdentity: Inserting Anybody into Anywhere at First Sight
Qinghe Wang, Xu Jia, Xiaomin Li +4
Recent advances in large pretrained text-to-image models have shown unprecedented capabilities for high-quality human-centric generation, however, customizing face identity is stil…
HS-Diffusion: Semantic-Mixing Diffusion for Head Swapping
Qinghe Wang, Lijie Liu, Miao Hua +5
Image-based head swapping task aims to stitch a source head to another source body flawlessly. This seldom-studied task faces two major challenges: 1) Preserving the head and body…