1 citations · 1 across the 13 of their papers we have counts for
10 papers · 1 filter
DRT: Dense Reasoning Trace for Efficient and Grounded Multimodal Reasoning
Wan Xu, Yuanfan Guo, Kevin Han +2
Despite the remarkable progress in Multimodal Large Language Models (MLLMs), prevailing Chain-of-Thought (CoT) paradigms remain confined to the natural-language expression space. C…
AnE: Pushing the Reasoning Frontier of Multimodal LLMs via Anchor Evolution
Zehao Wang, Yihan Zeng, Zidong Gong +5
Post-training via Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL) is crucial for enhancing reasoning in Multimodal Large Language Models (MLLMs), yet existing paradigm…
SlowFocus: Enhancing Fine-grained Temporal Understanding in Video LLM
Ming Nie, Dan Ding, Chunwei Wang +4
Large language models (LLMs) have demonstrated exceptional capabilities in text understanding, which has paved the way for their expansion into video LLMs (Vid-LLMs) to analyze vid…
VTimeCoT: Thinking by Drawing for Video Temporal Grounding and Reasoning
Jinglei Zhang, Yuanfan Guo, Rolandos Alexandros Potamias +3
In recent years, video question answering based on multimodal large language models (MLLM) has garnered considerable attention, due to the benefits from the substantial advancement…
GLaVE-Cap: Global-Local Aligned Video Captioning with Vision Expert Integration
Wan Xu, Feng Zhu, Yihan Zeng +4
Video detailed captioning aims to generate comprehensive video descriptions to facilitate video understanding. Recently, most efforts in the video detailed captioning community hav…
Brick-Diffusion: Generating Long Videos with Brick-to-Wall Denoising
Yunlong Yuan, Yuanfan Guo, Chunwei Wang +2
Recent advances in diffusion models have greatly improved text-driven video generation. However, training models for long video generation demands significant computational power a…
EasyControl: Transfer ControlNet to Video Diffusion for Controllable Generation and Interpolation
Cong Wang, Jiaxi Gu, Panwen Hu +5
Following the advancements in text-guided image generation technology exemplified by Stable Diffusion, video generation is gaining increased attention in the academic community. Ho…
HumanRefiner: Benchmarking Abnormal Human Generation and Refining with Coarse-to-fine Pose-Reversible Guidance
Guian Fang, Wenbiao Yan, Yuanfan Guo +5
Text-to-image diffusion models have significantly advanced in conditional image generation. However, these models usually struggle with accurately rendering images featuring humans…
PanGu-Draw: Advancing Resource-Efficient Text-to-Image Synthesis with Time-Decoupled Training and Reusable Coop-Diffusion
Guansong Lu, Yuanfan Guo, Jianhua Han +7
Current large-scale diffusion models represent a giant leap forward in conditional image synthesis, capable of interpreting diverse cues like text, human poses, and edges. However,…
DreamVideo: High-Fidelity Image-to-Video Generation with Image Retention and Text Guidance
Cong Wang, Jiaxi Gu, Panwen Hu +3
Image-to-video generation, which aims to generate a video starting from a given reference image, has drawn great attention. Existing methods try to extend pre-trained text-guided i…