14 papers · 1 filter
EventLens: Event-Structure Reinforcement Learning for Video Understanding
Guowen Zhang, Boshen Xu, Zihao Yue +6
Recent multimodal large language models (MLLMs) achieve strong results on video question answering, yet often fail to recover the temporal structure that makes a video coherent. Th…
Omni-o3: Deep Nested Omnimodal Deduction for Deliberative Audio-Visual Reasoning
Zhicheng Zhang, Wentao Gu, Weicheng Wang +5
Omnimodal understanding entails a massive, highly redundant search space of cross-modal interactions, demanding focused and deliberative reasoning. Current reasoning paradigms rely…
LIVE: Leveraging Image Manipulation Priors for Instruction-based Video Editing
Weicheng Wang, Zhicheng Zhang, Zhongqi Zhang +6
Video editing aims to modify input videos according to user intent. Recently, end-to-end training methods have garnered widespread attention, constructing paired video editing data…
Beyond the Golden Data: Resolving the Motion-Vision Quality Dilemma via Timestep Selective Training
Xiangyang Luo, Qingyu Li, Yuming Li +6
Recent advances in video generation models have achieved impressive results. However, these models heavily rely on the use of high-quality data that combines both high visual quali…
Embed-RL: Reinforcement Learning for Reasoning-Driven Multimodal Embeddings
Haonan Jiang, Yuji Wang, Yongjie Zhu +5
Leveraging Multimodal Large Language Models (MLLMs) has become pivotal for advancing Universal Multimodal Embeddings (UME) in addressing diverse cross-modal tasks. Recent studies d…
PureCC: Pure Learning for Text-to-Image Concept Customization
Zhichao Liao, Xiaole Xian, Qingyu Li +7
Existing concept customization methods have achieved remarkable outcomes in high-fidelity and multi-concept customization. However, they often neglect the influence on the original…
KPM-Bench: A Kinematic Parsing Motion Benchmark for Fine-grained Motion-centric Video Understanding
Boda Lin, Yongjie Zhu, Xiaocheng Gong +2
Despite recent advancements, video captioning models still face significant limitations in accurately describing fine-grained motion details and suffer from severe hallucination is…
Analytic Score Optimization for Multi Dimension Video Quality Assessment
Boda Lin, Yongjie Zhu, Wenyu Qin +2
Video Quality Assessment (VQA) is evolving beyond single-number mean opinion score toward richer, multi-faceted evaluations of video content. In this paper, we present a large-scal…
FilmWeaver: Weaving Consistent Multi-Shot Videos with Cache-Guided Autoregressive Diffusion
Xiangyang Luo, Qingyu Li, Xiaokun Liu +7
Current video generation models perform well at single-shot synthesis but struggle with multi-shot videos, facing critical challenges in maintaining character and background consis…
VidEmo: Affective-Tree Reasoning for Emotion-Centric Video Foundation Models
Zhicheng Zhang, Weicheng Wang, Yongjie Zhu +4
Understanding and predicting emotion from videos has gathered significant attention in recent studies, driven by advancements in video large language models (VideoLLMs). While adva…
MODA: MOdular Duplex Attention for Multimodal Perception, Cognition, and Emotion Understanding
Zhicheng Zhang, Wuyou Xia, Chenxi Zhao +7
Multimodal large language models (MLLMs) recently showed strong capacity in integrating data among multiple modalities, empowered by a generalizable attention architecture. Advance…
SPF-Portrait: Towards Pure Text-to-Portrait Customization with Semantic Pollution-Free Fine-Tuning
Xiaole Xian, Zhichao Liao, Qingyu Li +6
Fine-tuning a pre-trained Text-to-Image (T2I) model on a tailored portrait dataset is the mainstream method for text-to-portrait customization. However, existing methods often seve…
HumanAesExpert: Advancing a Multi-Modality Foundation Model for Human Image Aesthetic Assessment
Zhichao Liao, Xiaokun Liu, Wenyu Qin +6
Image Aesthetic Assessment (IAA) is a long-standing and challenging research task. However, its subset, Human Image Aesthetic Assessment (HIAA), has been scarcely explored. To brid…
Improving Video Generation with Human Feedback
Jie Liu, Gongye Liu, Jiajun Liang +14
Video generation has achieved significant advances through rectified flow techniques, but issues like unsmooth motion and misalignment between videos and prompts persist. In this w…