7 papers
Visual Token Coding for Video Multimodal Large Language Models
Chenxin Fang, Tao Chen, JunChao You +3
In this paper, we propose a new token compression paradigm for video Multimodal Large Language Models (MLLMs), termed Visual Token Coding (VTC). Inspired by classical video coding…
QCA: Query- and Content-Aware Keyframe Selection for Long Video Understanding
Jun Peng, Baiyang Song, Jie Li +4
Video understanding is often plagued by severe temporal redundancy, where processing dense frame sequences is both semantically inefficient and computationally expensive. This chal…
Towards a Dynamic and Fixed-budget Memory Bank for Efficient Streaming Video Understanding
Baiyang Song, Yuli Lin, Qiong Wu +5
Currently, streaming video understanding is still a daunting task for existing \emph{multimodal large language models} (MLLMs). Its difficulties not only lie in handling the ever-i…
Towards Effective Long Video Understanding of Multimodal Large Language Models via One-shot Clip Retrieval
Tao Chen, Shaobo Ju, Qiong Wu +6
Due to excessive memory overhead, most Multimodal Large Language Models (MLLMs) can only process videos of limited frames. In this paper, we propose an effective and efficient para…
AdaFlow: Efficient Long Video Editing via Adaptive Attention Slimming And Keyframe Selection
Shuheng Zhang, Yuqi Liu, Hongbo Zhou +4
Despite great progress, text-driven long video editing is still notoriously challenging mainly due to excessive memory overhead. Although recent efforts have simplified this task i…
Fast Text-to-3D-Aware Face Generation and Manipulation via Direct Cross-modal Mapping and Geometric Regularization
Jinlu Zhang, Yiyi Zhou, Qiancheng Zheng +5
Text-to-3D-aware face (T3D Face) generation and manipulation is an emerging research hot spot in machine learning, which still suffers from low efficiency and poor quality. In this…
PixelFolder: An Efficient Progressive Pixel Synthesis Network for Image Generation
Jing He, Yiyi Zhou, Qi Zhang +5
Pixel synthesis is a promising research paradigm for image generation, which can well exploit pixel-wise prior knowledge for generation. However, existing methods still suffer from…