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Found 10 papers, 5 papers with code
Co-Speech Gesture Video Generation via Motion-Decoupled Diffusion Model
While previous works mostly generate structural human skeletons, resulting in the omission of appearance information, we focus on the direct generation of audio-driven co-speech gesture videos in this work.
VastGaussian: Vast 3D Gaussians for Large Scene Reconstruction
Existing NeRF-based methods for large scene reconstruction often have limitations in visual quality and rendering speed.
RealDex: Towards Human-like Grasping for Robotic Dexterous Hand
In this paper, we introduce RealDex, a pioneering dataset capturing authentic dexterous hand grasping motions infused with human behavioral patterns, enriched by multi-view and multimodal visual data.
YAYI 2: Multilingual Open-Source Large Language Models
As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world tasks, and even have been regarded as a potential path to the artificial general intelligence.
Semantics-aware Motion Retargeting with Vision-Language Models
Capturing and preserving motion semantics is essential to motion retargeting between animation characters.
A unified consensus-based parallel ADMM algorithm for high-dimensional regression with combined regularizations
The parallel alternating direction method of multipliers (ADMM) algorithm is widely recognized for its effectiveness in handling large-scale datasets stored in a distributed manner, making it a popular choice for solving statistical learning models.
UnifiedGesture: A Unified Gesture Synthesis Model for Multiple Skeletons
The automatic co-speech gesture generation draws much attention in computer animation.
The DiffuseStyleGesture+ entry to the GENEA Challenge 2023
In this paper, we introduce the DiffuseStyleGesture+, our solution for the Generation and Evaluation of Non-verbal Behavior for Embodied Agents (GENEA) Challenge 2023, which aims to foster the development of realistic, automated systems for generating conversational gestures.
Learning Causal Representation for Training Cross-Domain Pose Estimator via Generative Interventions
In this work, we take a step towards training robust models for cross-domain pose estimation task, which brings together ideas from causal representation learning and generative adversarial networks.
High-Order Residual Network for Light Field Super-Resolution
In this paper, we propose a novel high-order residual network to learn the geometric features hierarchically from the LF for reconstruction.
