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VADB: A Large-Scale Video Aesthetic Database with Professional and Multi-Dimensional Annotations
Qianqian Qiao, DanDan Zheng, Yihang Bo +7
Video aesthetic assessment, a vital area in multimedia computing, integrates computer vision with human cognition. Its progress is limited by the lack of standardized datasets and…
PruneHal: Reducing Hallucinations in Multi-modal Large Language Models through Adaptive KV Cache Pruning
Fengyuan Sun, Hui Chen, Xinhao Xu +5
While multi-modal large language models (MLLMs) have made significant progress in recent years, the issue of hallucinations remains a major challenge. To mitigate this phenomenon,…
Ming-Flash-Omni: A Sparse, Unified Architecture for Multimodal Perception and Generation
Inclusion AI, :, Bowen Ma +73
We propose Ming-Flash-Omni, an upgraded version of Ming-Omni, built upon a sparser Mixture-of-Experts (MoE) variant of Ling-Flash-2.0 with 100 billion total parameters, of which on…
ARGenSeg: Image Segmentation with Autoregressive Image Generation Model
Xiaolong Wang, Lixiang Ru, Ziyuan Huang +4
We propose a novel AutoRegressive Generation-based paradigm for image Segmentation (ARGenSeg), achieving multimodal understanding and pixel-level perception within a unified framew…
Video Virtual Try-on with Conditional Diffusion Transformer Inpainter
Cheng Zou, Senlin Cheng, Bolei Xu +4
Video virtual try-on aims to naturally fit a garment to a target person in consecutive video frames. It is a challenging task, on the one hand, the output video should be in good s…
VideoMAR: Autoregressive Video Generatio with Continuous Tokens
Hu Yu, Biao Gong, Hangjie Yuan +5
Masked-based autoregressive models have demonstrated promising image generation capability in continuous space. However, their potential for video generation remains under-explored…
Ming-Lite-Uni: Advancements in Unified Architecture for Natural Multimodal Interaction
Inclusion AI, Biao Gong, Cheng Zou +14
We introduce Ming-Lite-Uni, an open-source multimodal framework featuring a newly designed unified visual generator and a native multimodal autoregressive model tailored for unifyi…
Ming-Omni: A Unified Multimodal Model for Perception and Generation
Inclusion AI, Biao Gong, Cheng Zou +55
We propose Ming-Omni, a unified multimodal model capable of processing images, text, audio, and video, while demonstrating strong proficiency in both speech and image generation. M…
SynMotion: Semantic-Visual Adaptation for Motion Customized Video Generation
Shuai Tan, Biao Gong, Yujie Wei +8
Diffusion-based video motion customization facilitates the acquisition of human motion representations from a few video samples, while achieving arbitrary subjects transfer through…