2 citations · 4 across the 8 of their papers we have counts for
9 papers
OmniScript: Towards Audio-Visual Script Generation for Long-Form Cinematic Video
Junfu Pu, Yuxin Chen, Teng Wang +1
Current multimodal large language models (MLLMs) have demonstrated remarkable capabilities in short-form video understanding, yet translating long-form cinematic videos into detail…
TimeLens: Rethinking Video Temporal Grounding with Multimodal LLMs
Jun Zhang, Teng Wang, Yuying Ge +4
This paper does not introduce a novel method but instead establishes a straightforward, incremental, yet essential baseline for video temporal grounding (VTG), a core capability in…
ARC-Chapter: Structuring Hour-Long Videos into Navigable Chapters and Hierarchical Summaries
Junfu Pu, Teng Wang, Yixiao Ge +3
The proliferation of hour-long videos (e.g., lectures, podcasts, documentaries) has intensified demand for efficient content structuring. However, existing approaches are constrain…
From Denoising to Refining: A Corrective Framework for Vision-Language Diffusion Model
Yatai Ji, Teng Wang, Yuying Ge +4
Discrete diffusion models have emerged as a promising direction for vision-language tasks, offering bidirectional context modeling and theoretical parallelization. However, their p…
AudioStory: Generating Long-Form Narrative Audio with Large Language Models
Yuxin Guo, Teng Wang, Yuying Ge +4
Recent advances in text-to-audio (TTA) generation excel at synthesizing short audio clips but struggle with long-form narrative audio, which requires temporal coherence and composi…
ARC-Hunyuan-Video-7B: Structured Video Comprehension of Real-World Shorts
Yuying Ge, Yixiao Ge, Chen Li +15
Real-world user-generated short videos, especially those distributed on platforms such as WeChat Channel and TikTok, dominate the mobile internet. However, current large multimodal…
Video-Holmes: Can MLLM Think Like Holmes for Complex Video Reasoning?
Junhao Cheng, Yuying Ge, Teng Wang +3
Recent advances in CoT reasoning and RL post-training have been reported to enhance video reasoning capabilities of MLLMs. This progress naturally raises a question: can these mode…
GenHancer: Imperfect Generative Models are Secretly Strong Vision-Centric Enhancers
Shijie Ma, Yuying Ge, Teng Wang +3
The synergy between generative and discriminative models receives growing attention. While discriminative Contrastive Language-Image Pre-Training (CLIP) excels in high-level semant…
BAISeg: Boundary Assisted Weakly Supervised Instance Segmentation
Tengbo Wang, Yu Bai
How to extract instance-level masks without instance-level supervision is the main challenge of weakly supervised instance segmentation (WSIS). Popular WSIS methods estimate a disp…