6 citations · 11 across the 18 of their papers we have counts for
18 papers
Hunyuan3D-Buffalo 1.0: A Unified Multimodal Model for Scalable 3D Generation, Understanding, and Editing
Junliang Ye, Kenkun Liu, Guocun Wang +13
Recent advances in image generation have demonstrated the potential of unified multimodal models that integrate understanding, generation, and editing. However, unified 3D modeling…
JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space
Xinnan Zhu, Ruijie Xu, Jiayu Ying +4
Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelines, resulting in high test-time…
WorldVLN: Autoregressive World Action Model for Aerial Vision-Language Navigation
Baining Zhao, Jiacheng Xu, Weicheng Feng +13
Aerial vision-language navigation (VLN) requires agents to follow natural-language instructions through closed-loop perception and action in 3D environments. We argue that aerial V…
Forecast-aware Gaussian Splatting for Predictive 3D Representation in Language-Guided Pick-and-Place Manipulation
Kaixin Jia, Jiacheng Xu
We introduce Forecast-aware Gaussian Splatting (Forecast-GS), a predictive 3D representation framework for language-conditioned robotic manipulation. While recent manipulation syst…
How Far Are Large Multimodal Models from Human-Level Spatial Action? A Benchmark for Goal-Oriented Embodied Navigation in Urban Airspace
Baining Zhao, Ziyou Wang, Jianjie Fang +8
Large multimodal models (LMMs) show strong visual-linguistic reasoning but their capacity for spatial decision-making and action remains unclear. In this work, we investigate wheth…
Grasp as You Dream: Imitating Functional Grasping from Generated Human Demonstrations
Chao Tang, Jiacheng Xu, Haofei Lu +4
Building generalist robots capable of performing functional grasping in everyday, open-world environments remains a significant challenge due to the vast diversity of objects and t…
HY3D-Bench: Generation of 3D Assets
Team Hunyuan3D, :, Bowen Zhang +22
While recent advances in neural representations and generative models have revolutionized 3D content creation, the field remains constrained by significant data processing bottlene…
A Comparative Evaluation of Large Vision-Language Models for 2D Object Detection under SOTIF Conditions
Ji Zhou, Yilin Ding, Yongqi Zhao +4
Reliable environmental perception remains one of the main obstacles for safe operation of automated vehicles. Safety of the Intended Functionality (SOTIF) concerns safety risks fro…
P3-SAM: Native 3D Part Segmentation
Changfeng Ma, Yang Li, Xinhao Yan +7
Segmenting 3D assets into their constituent parts is crucial for enhancing 3D understanding, facilitating model reuse, and supporting various applications such as part generation.…
X-Part: high fidelity and structure coherent shape decomposition
Xinhao Yan, Jiachen Xu, Yang Li +8
Generating 3D shapes at part level is pivotal for downstream applications such as mesh retopology, UV mapping, and 3D printing. However, existing part-based generation methods ofte…
Compound Figure Separation of Biomedical Images: Mining Large Datasets for Self-supervised Learning
Tianyuan Yao, Chang Qu, Jun Long +13
With the rapid development of self-supervised learning (e.g., contrastive learning), the importance of having large-scale images (even without annotations) for training a more gene…
Holistic Fine-grained GGS Characterization: From Detection to Unbalanced Classification
Yuzhe Lu, Haichun Yang, Zuhayr Asad +5
Recent studies have demonstrated the diagnostic and prognostic values of global glomerulosclerosis (GGS) in IgA nephropathy, aging, and end-stage renal disease. However, the fine-g…
Semi-Supervised Contrastive Learning for Remote Sensing: Identifying Ancient Urbanization in the South Central Andes
Jiachen Xu, Junlin Guo, James Zimmer-Dauphinee +7
Archaeology has long faced fundamental issues of sampling and scalar representation. Traditionally, the local-to-regional-scale views of settlement patterns are produced through sy…
Exploring Versatile Prior for Human Motion via Motion Frequency Guidance
Jiachen Xu, Min Wang, Jingyu Gong +4
Prior plays an important role in providing the plausible constraint on human motion. Previous works design motion priors following a variety of paradigms under different circumstan…
Omni-supervised Point Cloud Segmentation via Gradual Receptive Field Component Reasoning
Jingyu Gong, Jiachen Xu, Xin Tan +4
Hidden features in neural network usually fail to learn informative representation for 3D segmentation as supervisions are only given on output prediction, while this can be solved…
Boundary-Aware Geometric Encoding for Semantic Segmentation of Point Clouds
Jingyu Gong, Jiachen Xu, Xin Tan +4
Boundary information plays a significant role in 2D image segmentation, while usually being ignored in 3D point cloud segmentation where ambiguous features might be generated in fe…
Analysis on DeepLabV3+ Performance for Automatic Steel Defects Detection
Zheng Nie, Jiachen Xu, Shengchang Zhang
Our works experimented DeepLabV3+ with different backbones on a large volume of steel images aiming to automatically detect different types of steel defects. Our methods applied ra…
SceneEncoder: Scene-Aware Semantic Segmentation of Point Clouds with A Learnable Scene Descriptor
Jiachen Xu, Jingyu Gong, Jie Zhou +3
Besides local features, global information plays an essential role in semantic segmentation, while recent works usually fail to explicitly extract the meaningful global information…