41 citations · 42 across the 8 of their papers we have counts for
7 papers · 1 filter
Beyond Retrieval: Progressive Latent Memory Evolution for Streaming Video Understanding
Hongyu Qu, Guangming Yao, Ling Xing +7
Streaming video understanding requires multimodal large language models (MLLMs) to process continuous visual inputs and respond to user queries under strict causality and bounded m…
VideoGAIA: A Benchmark for General AI Assistants on Agentic Video Understanding
Fan Zhang, Guangming Yao, Jinyang Wu +6
Video understanding is a fundamental task for evaluating the capabilities of multimodal large language models (MLLMs). However, existing leading models have already achieved approx…
MemDreamer: Decoupling Perception and Reasoning for Long Video Understanding via Hierarchical Graph Memory and Agentic Retrieval Mechanism
Cong Chen, Guo Gan, Kaixiang Ji +7
Current Vision-Language Models struggle with hours-long videos because processing full-length visual sequences induces prohibitive token explosion and attention dilution. To overco…
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…
Learning Implicit Body Representations from Double Diffusion Based Neural Radiance Fields
Guangming Yao, Hongzhi Wu, Yi Yuan +3
In this paper, we present a novel double diffusion based neural radiance field, dubbed DD-NeRF, to reconstruct human body geometry and render the human body appearance in novel vie…
One-shot Face Reenactment Using Appearance Adaptive Normalization
Guangming Yao, Yi Yuan, Tianjia Shao +5
The paper proposes a novel generative adversarial network for one-shot face reenactment, which can animate a single face image to a different pose-and-expression (provided by a dri…
Mesh Guided One-shot Face Reenactment using Graph Convolutional Networks
Guangming Yao, Yi Yuan, Tianjia Shao +1
Face reenactment aims to animate a source face image to a different pose and expression provided by a driving image. Existing approaches are either designed for a specific identity…