37 citations · 107 across the 15 of their papers we have counts for
17 papers
Hy-Embodied-0.5-VLA: From Vision-Language-Action Models to a Real-World Robot Learning Stack
He Zhang, Lingzhu Xiang, Haitao Lin +23
In this report, we present Hy-Embodied-0.5-VLA, abbreviated as HyVLA-0.5, an end-to-end system that spans the full robot learning stack: data collection, model design, continued pr…
Hy-Embodied-VLM-1.0: Efficient Physical-World Agents
Ziyi Wang, Xumin Yu, Yongming Rao +19
Building capable embodied agents requires not only multimodal perception and understanding, but also agentic capabilities for reasoning about actions, adapting to evolving situatio…
ViQ: Text-Aligned Visual Quantized Representations at Any Resolution
Xumin Yu, Zuyan Liu, Zhenyu Yang +5
A unified representation for text and vision is a natural pursuit, as it enables simpler multimodal modeling and more efficient training. However, representing images as discrete s…
GEM: Generative Supervision Helps Embodied Intelligence
Ruowen Zhao, Bangguo Li, Zuyan Liu +9
Embodied Vision-Language Models (VLMs) have demonstrated impressive performance and generalization in robotics, particularly within Vision-Language-Action frameworks. However, a si…
HY-Embodied-0.5: Embodied Foundation Models for Real-World Agents
Tencent Robotics X, HY Vision Team, : +20
We introduce HY-Embodied-0.5, a family of foundation models specifically designed for real-world embodied agents. To bridge the gap between general Vision-Language Models (VLMs) an…
Spatial-TTT: Streaming Visual-based Spatial Intelligence with Test-Time Training
Fangfu Liu, Diankun Wu, Jiawei Chi +7
Humans perceive and understand real-world spaces through a stream of visual observations. Therefore, the ability to streamingly maintain and update spatial evidence from potentiall…
Vision Generalist Model: A Survey
Ziyi Wang, Yongming Rao, Shuofeng Sun +8
Recently, we have witnessed the great success of the generalist model in natural language processing. The generalist model is a general framework trained with massive data and is a…
XMask3D: Cross-modal Mask Reasoning for Open Vocabulary 3D Semantic Segmentation
Ziyi Wang, Yanbo Wang, Xumin Yu +2
Existing methodologies in open vocabulary 3D semantic segmentation primarily concentrate on establishing a unified feature space encompassing 3D, 2D, and textual modalities. Nevert…
FlowTurbo: Towards Real-time Flow-Based Image Generation with Velocity Refiner
Wenliang Zhao, Minglei Shi, Xumin Yu +2
Building on the success of diffusion models in visual generation, flow-based models reemerge as another prominent family of generative models that have achieved competitive or bett…
OpenVoice: Versatile Instant Voice Cloning
Zengyi Qin, Wenliang Zhao, Xumin Yu +1
We introduce OpenVoice, a versatile voice cloning approach that requires only a short audio clip from the reference speaker to replicate their voice and generate speech in multiple…
Take-A-Photo: 3D-to-2D Generative Pre-training of Point Cloud Models
Ziyi Wang, Xumin Yu, Yongming Rao +2
With the overwhelming trend of mask image modeling led by MAE, generative pre-training has shown a remarkable potential to boost the performance of fundamental models in 2D vision.…
AdaPoinTr: Diverse Point Cloud Completion with Adaptive Geometry-Aware Transformers
Xumin Yu, Yongming Rao, Ziyi Wang +2
In this paper, we present a new method that reformulates point cloud completion as a set-to-set translation problem and design a new model, called PoinTr, which adopts a Transforme…
P2P: Tuning Pre-trained Image Models for Point Cloud Analysis with Point-to-Pixel Prompting
Ziyi Wang, Xumin Yu, Yongming Rao +2
Nowadays, pre-training big models on large-scale datasets has become a crucial topic in deep learning. The pre-trained models with high representation ability and transferability a…
Learning from Temporal Spatial Cubism for Cross-Dataset Skeleton-based Action Recognition
Yansong Tang, Xingyu Liu, Xumin Yu +3
Rapid progress and superior performance have been achieved for skeleton-based action recognition recently. In this article, we investigate this problem under a cross-dataset settin…
SemAffiNet: Semantic-Affine Transformation for Point Cloud Segmentation
Ziyi Wang, Yongming Rao, Xumin Yu +2
Conventional point cloud semantic segmentation methods usually employ an encoder-decoder architecture, where mid-level features are locally aggregated to extract geometric informat…
FineDiving: A Fine-grained Dataset for Procedure-aware Action Quality Assessment
Jinglin Xu, Yongming Rao, Xumin Yu +3
Most existing action quality assessment methods rely on the deep features of an entire video to predict the score, which is less reliable due to the non-transparent inference proce…
PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
Xumin Yu, Yongming Rao, Ziyi Wang +3
Point clouds captured in real-world applications are often incomplete due to the limited sensor resolution, single viewpoint, and occlusion. Therefore, recovering the complete poin…