67 citations · 145 across the 13 of their papers we have counts for
14 papers
Has GPT-6-Astra Achieved Embodied Intelligence?
SenseNova, Joint Research Team, : +60
GPT-6-Astra demonstrates a level of competence in robotic manipulation and navigation that challenges the conventional paradigm of building specialized models for individual tasks…
ExToken: Structured Exploration for Efficient Vision-Language-Action Reinforcement Fine-tuning
Yilun Kong, Yunpeng Qing, Guozheng Ma +4
Reinforcement Learning (RL) has demonstrated significant potential for improving Vision-Language-Action (VLA) models on complex manipulation tasks. However, its practical scalabili…
ACE-Brain-0.5: A Unified Embodied Foundational Model for Physical Agentic AI
Brain Team, Ziyang Gong, Haoming Gu +28
Embodied AI is moving from isolated perception or action modules toward physical agents that understand, plan under goals, act through robot bodies, monitor progress, and improve f…
ACE-Brain-0: Spatial Intelligence as a Shared Scaffold for Universal Embodiments
Ziyang Gong, Zehang Luo, Anke Tang +21
Universal embodied intelligence demands robust generalization across heterogeneous embodiments, such as autonomous driving, robotics, and unmanned aerial vehicles (UAVs). However,…
Compositional 3D Human-Object Neural Animation
Zhi Hou, Baosheng Yu, Dacheng Tao
Human-object interactions (HOIs) are crucial for human-centric scene understanding applications such as human-centric visual generation, AR/VR, and robotics. Since existing methods…
AniPixel: Towards Animatable Pixel-Aligned Human Avatar
Jinlong Fan, Jing Zhang, Zhi Hou +1
Although human reconstruction typically results in human-specific avatars, recent 3D scene reconstruction techniques utilizing pixel-aligned features show promise in generalizing t…
Memorizing Complementation Network for Few-Shot Class-Incremental Learning
Zhong Ji, Zhishen Hou, Xiyao Liu +2
Few-shot Class-Incremental Learning (FSCIL) aims at learning new concepts continually with only a few samples, which is prone to suffer the catastrophic forgetting and overfitting…
BatchFormerV2: Exploring Sample Relationships for Dense Representation Learning
Zhi Hou, Baosheng Yu, Chaoyue Wang +2
Attention mechanisms have been very popular in deep neural networks, where the Transformer architecture has achieved great success in not only natural language processing but also…
BatchFormer: Learning to Explore Sample Relationships for Robust Representation Learning
Zhi Hou, Baosheng Yu, Dacheng Tao
Despite the success of deep neural networks, there are still many challenges in deep representation learning due to the data scarcity issues such as data imbalance, unseen distribu…
Discovering Human-Object Interaction Concepts via Self-Compositional Learning
Zhi Hou, Baosheng Yu, Dacheng Tao
A comprehensive understanding of human-object interaction (HOI) requires detecting not only a small portion of predefined HOI concepts (or categories) but also other reasonable HOI…
Information Symmetry Matters: A Modal-Alternating Propagation Network for Few-Shot Learning
Zhong Ji, Zhishen Hou, Xiyao Liu +2
Semantic information provides intra-class consistency and inter-class discriminability beyond visual concepts, which has been employed in Few-Shot Learning (FSL) to achieve further…
Affordance Transfer Learning for Human-Object Interaction Detection
Zhi Hou, Baosheng Yu, Yu Qiao +2
Reasoning the human-object interactions (HOI) is essential for deeper scene understanding, while object affordances (or functionalities) are of great importance for human to discov…
Detecting Human-Object Interaction via Fabricated Compositional Learning
Zhi Hou, Baosheng Yu, Yu Qiao +2
Human-Object Interaction (HOI) detection, inferring the relationships between human and objects from images/videos, is a fundamental task for high-level scene understanding. Howeve…
Visual Compositional Learning for Human-Object Interaction Detection
Zhi Hou, Xiaojiang Peng, Yu Qiao +1
Human-Object interaction (HOI) detection aims to localize and infer relationships between human and objects in an image. It is challenging because an enormous number of possible co…