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cs.CV2026

PortraitGen: Exemplar-Driven GRPO with Dual-Reward Guidance for Photorealistic Portrait Generation

Xiaomin Li, Qian Liang, Yinan Li +5

Reinforcement Learning like Group Relative Policy Optimization (GRPO) has significantly advanced text-to-image post-training. However, current methods often favor superficial aesth…

cs.CV2026

Mem-World: Memory-Augmented Action-Conditioned World Models for Persistent Robot Manipulation

Zirui Zheng, Jiaqian Yu, Xiongfeng Peng +7

Action-conditioned world models have emerged as a promising paradigm for robot learning, offering a scalable alternative to costly real-world experimentation by generating action-c…

cs.CV2026

Ego-InBetween: Generating Object State Transitions in Ego-Centric Videos

Mengmeng Ge, Takashi Isobe, Xu Jia +7

Understanding physical transformation processes is crucial for both human cognition and artificial intelligence systems, particularly from an egocentric perspective, which serves a…

cs.CV2026

Seek-and-Solve: Benchmarking MLLMs for Visual Clue-Driven Reasoning in Daily Scenarios

Xiaomin Li, Tala Wang, Zichen Zhong +7

Daily scenarios are characterized by visual richness, requiring Multimodal Large Language Models (MLLMs) to filter noise and identify decisive visual clues for accurate reasoning.…

cs.CV2025

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…

cs.CV2025

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-…