2 citations · 2 across the 5 of their papers we have counts for
5 papers
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…
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…
Versatile Multimodal Controls for Expressive Talking Human Animation
Zheng Qin, Ruobing Zheng, Yabing Wang +5
In filmmaking, directors typically allow actors to perform freely based on the script before providing specific guidance on how to present key actions. AI-generated content faces s…
LokiTalk: Learning Fine-Grained and Generalizable Correspondences to Enhance NeRF-based Talking Head Synthesis
Tianqi Li, Ruobing Zheng, Bonan Li +4
Despite significant progress in talking head synthesis since the introduction of Neural Radiance Fields (NeRF), visual artifacts and high training costs persist as major obstacles…
Ditto: Motion-Space Diffusion for Controllable Realtime Talking Head Synthesis
Tianqi Li, Ruobing Zheng, Minghui Yang +2
Recent advances in diffusion models have endowed talking head synthesis with subtle expressions and vivid head movements, but have also led to slow inference speed and insufficient…