3 citations · 7 across the 11 of their papers we have counts for
12 papers
Zero-Shot Audio-Visual Editing via Cross-Modal Delta Denoising
Yan-Bo Lin, Kevin Lin, Zhengyuan Yang +6
In this paper, we introduce zero-shot audio-video editing, a novel task that requires transforming original audio-visual content to align with a specified textual prompt without ad…
LiVOS: Light Video Object Segmentation with Gated Linear Matching
Qin Liu, Jianfeng Wang, Zhengyuan Yang +4
Semi-supervised video object segmentation (VOS) has been largely driven by space-time memory (STM) networks, which store past frame features in a spatiotemporal memory to segment t…
GenXD: Generating Any 3D and 4D Scenes
Yuyang Zhao, Chung-Ching Lin, Kevin Lin +6
Recent developments in 2D visual generation have been remarkably successful. However, 3D and 4D generation remain challenging in real-world applications due to the lack of large-sc…
SlowFast-VGen: Slow-Fast Learning for Action-Driven Long Video Generation
Yining Hong, Beide Liu, Maxine Wu +9
Human beings are endowed with a complementary learning system, which bridges the slow learning of general world dynamics with fast storage of episodic memory from a new experience.…
EditRoom: LLM-parameterized Graph Diffusion for Composable 3D Room Layout Editing
Kaizhi Zheng, Xiaotong Chen, Xuehai He +7
Given the steep learning curve of professional 3D software and the time-consuming process of managing large 3D assets, language-guided 3D scene editing has significant potential in…
MM-Vet v2: A Challenging Benchmark to Evaluate Large Multimodal Models for Integrated Capabilities
Weihao Yu, Zhengyuan Yang, Lingfeng Ren +7
MM-Vet, with open-ended vision-language questions targeting at evaluating integrated capabilities, has become one of the most popular benchmarks for large multimodal model evaluati…
MMWorld: Towards Multi-discipline Multi-faceted World Model Evaluation in Videos
Xuehai He, Weixi Feng, Kaizhi Zheng +11
Multimodal Language Language Models (MLLMs) demonstrate the emerging abilities of "world models" -- interpreting and reasoning about complex real-world dynamics. To assess these ab…
IDOL: Unified Dual-Modal Latent Diffusion for Human-Centric Joint Video-Depth Generation
Yuanhao Zhai, Kevin Lin, Linjie Li +7
Significant advances have been made in human-centric video generation, yet the joint video-depth generation problem remains underexplored. Most existing monocular depth estimation…
Motion Consistency Model: Accelerating Video Diffusion with Disentangled Motion-Appearance Distillation
Yuanhao Zhai, Kevin Lin, Zhengyuan Yang +6
Image diffusion distillation achieves high-fidelity generation with very few sampling steps. However, applying these techniques directly to video diffusion often results in unsatis…
List Items One by One: A New Data Source and Learning Paradigm for Multimodal LLMs
An Yan, Zhengyuan Yang, Junda Wu +8
Set-of-Mark (SoM) Prompting unleashes the visual grounding capability of GPT-4V, by enabling the model to associate visual objects with tags inserted on the image. These tags, mark…
Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition
Jielin Qiu, William Han, Winfred Wang +6
Open-domain real-world entity recognition is essential yet challenging, involving identifying various entities in diverse environments. The lack of a suitable evaluation dataset ha…
MMSum: A Dataset for Multimodal Summarization and Thumbnail Generation of Videos
Jielin Qiu, Jiacheng Zhu, William Han +9
Multimodal summarization with multimodal output (MSMO) has emerged as a promising research direction. Nonetheless, numerous limitations exist within existing public MSMO datasets,…