7 papers
X-Foresight: A Joint Vision-Action Causal Forecasting Network via Predictive World Modeling
Baolu Li, Jingyu Qian, Rui Guo +17
Physical world knowledge resides mainly in videos. Equipping Vision-Language-Action (VLA) models with such knowledge is fundamental for safe and generalizable planning. Predictive…
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…
Towards Anatomically Plausible Human Image Generation via Synthetic Localized Preferences
Bao Li, Yuliang Xiu, Zhen Liu
Large-scale text-to-image foundation models have achieved remarkable visual realism, yet generating human images with correct anatomical structures remains challenging. Existing ap…
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…
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…
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-…