7 citations · 16 across the 58 of their papers we have counts for
26 papers · 1 filter
3SGen: Unified Subject, Style, and Structure-Driven Image Generation with Adaptive Task-specific Memory
Xinyang Song, Libin Wang, Weining Wang +6
Recent image generation approaches often address subject, style, and structure-driven conditioning in isolation, leading to feature entanglement and limited task transferability. I…
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…
Ming-UniAudio: Speech LLM for Joint Understanding, Generation and Editing with Unified Representation
Canxiang Yan, Chunxiang Jin, Dawei Huang +22
Existing speech models suffer from competing requirements on token representations by understanding and generation tasks. This discrepancy in representation prevents speech languag…
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-UniVision: Joint Image Understanding and Generation with a Unified Continuous Tokenizer
Ziyuan Huang, DanDan Zheng, Cheng Zou +13
Visual tokenization remains a core challenge in unifying visual understanding and generation within the autoregressive paradigm. Existing methods typically employ tokenizers in dis…
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…
UniAlignment: Semantic Alignment for Unified Image Generation, Understanding, Manipulation and Perception
Xinyang Song, Libin Wang, Weining Wang +5
The remarkable success of diffusion models in text-to-image generation has sparked growing interest in expanding their capabilities to a variety of multi-modal tasks, including ima…
GUI-Shepherd: Reliable Process Reward and Verification for Long-Sequence GUI Tasks
Cong Chen, Kaixiang Ji, Hao Zhong +9
Autonomous agents for long-sequence Graphical User Interface tasks are hindered by sparse rewards and the intractable credit assignment problem. To address these challenges, we int…
HieraTok: Multi-Scale Visual Tokenizer Improves Image Reconstruction and Generation
Cong Chen, Ziyuan Huang, Cheng Zou +6
In this work, we present HieraTok, a novel multi-scale Vision Transformer (ViT)-based tokenizer that overcomes the inherent limitation of modeling single-scale representations. Thi…
Structuring GUI Elements through Vision Language Models: Towards Action Space Generation
Yi Xu, Yesheng Zhang, Jiajia Liu +1
Multimodal large language models (MLLMs) have emerged as pivotal tools in enhancing human-computer interaction. In this paper we focus on the application of MLLMs in the field of g…
HumanSense: From Multimodal Perception to Empathetic Context-Aware Responses through Reasoning MLLMs
Zheng Qin, Ruobing Zheng, Yabing Wang +4
While Multimodal Large Language Models (MLLMs) show immense promise for achieving truly human-like interactions, progress is hindered by the lack of fine-grained evaluation framewo…
CasP: Improving Semi-Dense Feature Matching Pipeline Leveraging Cascaded Correspondence Priors for Guidance
Peiqi Chen, Lei Yu, Yi Wan +9
Semi-dense feature matching methods have shown strong performance in challenging scenarios. However, the existing pipeline relies on a global search across the entire feature map t…
SkySense V2: A Unified Foundation Model for Multi-modal Remote Sensing
Yingying Zhang, Lixiang Ru, Kang Wu +4
The multi-modal remote sensing foundation model (MM-RSFM) has significantly advanced various Earth observation tasks, such as urban planning, environmental monitoring, and natural…
M2-Reasoning: Empowering MLLMs with Unified General and Spatial Reasoning
Inclusion AI, :, Fudong Wang +12
Recent advancements in Multimodal Large Language Models (MLLMs), particularly through Reinforcement Learning with Verifiable Rewards (RLVR), have significantly enhanced their reaso…
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…
Reversing Flow for Image Restoration
Haina Qin, Wenyang Luo, Libin Wang +5
Image restoration aims to recover high-quality (HQ) images from degraded low-quality (LQ) ones by reversing the effects of degradation. Existing generative models for image restora…
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…
ACTIVE-o3: Empowering MLLMs with Active Perception via Pure Reinforcement Learning
Muzhi Zhu, Hao Zhong, Canyu Zhao +9
Active vision, also known as active perception, refers to actively selecting where and how to look in order to gather task-relevant information. It is a critical component of effic…
When Large Vision-Language Model Meets Large Remote Sensing Imagery: Coarse-to-Fine Text-Guided Token Pruning
Junwei Luo, Yingying Zhang, Xue Yang +5
Efficient vision-language understanding of large Remote Sensing Images (RSIs) is meaningful but challenging. Current Large Vision-Language Models (LVLMs) typically employ limited p…
M2-omni: Advancing Omni-MLLM for Comprehensive Modality Support with Competitive Performance
Qingpei Guo, Kaiyou Song, Zipeng Feng +9
We present M2-omni, a cutting-edge, open-source omni-MLLM that achieves competitive performance to GPT-4o. M2-omni employs a unified multimodal sequence modeling framework, which e…