1 citations · 1 across the 9 of their papers we have counts for
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OccluRank: Controllable Occlusion-Aware Layout-to-Image Generation by Adding Just an Ordinal Rank
Wenyang Hong, Yuan Wang, Yanbin Hao +5
Layout-to-image generation enables explicit spatial control through bounding-box layouts, yet bounding boxes specify only instance locations and cannot represent their occlusion or…
Uni-AdaVD: Universal Concept Erasure for Visual Generation via Orthogonal Value Decomposition
Qifan Zhou, Yuan Wang, Yanbin Hao +4
Visual generative models inevitably absorb undesirable concepts from uncurated pretraining data, making concept erasure essential for safe deployment. Existing erasure methods, how…
Think, then Score: Decoupled Reasoning and Scoring for Video Reward Modeling
Yuan Wang, Ouxiang Li, Yulong Xu +8
Recent advances in generative video models are increasingly driven by post-training and test-time scaling, both of which critically depend on the quality of video reward models (RM…
Frequency-Enhanced Dual-Subspace Networks for Few-Shot Fine-Grained Image Classification
Meijia Wang, Guochao Wang, Haozhen Chu +4
Few-shot fine-grained image classification aims to recognize subcategories with high visual similarity using only a limited number of annotated samples. Existing metric learning-ba…
UniVBench: Towards Unified Evaluation for Video Foundation Models
Jianhui Wei, Xiaotian Zhang, Yichen Li +6
Video foundation models aim to integrate video understanding, generation, editing, and instruction following within a single framework, making them a central direction for next-gen…
Enhancing Multi-Modal LLMs Reasoning via Difficulty-Aware Group Normalization
Jinghan Li, Junfeng Fang, Jinda Lu +5
Reinforcement Learning with Verifiable Rewards (RLVR) and Group Relative Policy Optimization (GRPO) have significantly advanced the reasoning capabilities of large language models.…
Thinking with Frames: Generative Video Distortion Evaluation via Frame Reward Model
Yuan Wang, Borui Liao, Huijuan Huang +5
Recent advances in video reward models and post-training strategies have improved text-to-video (T2V) generation. While these models typically assess visual quality, motion quality…
Easier Painting Than Thinking: Can Text-to-Image Models Set the Stage, but Not Direct the Play?
Ouxiang Li, Yuan Wang, Xinting Hu +7
Text-to-image (T2I) generation aims to synthesize images from textual prompts, which jointly specify what must be shown and imply what can be inferred, which thus correspond to two…