activity
20192025
most citedRelational Learning between Multiple Pulmonary Nodules via Deep Set Attention Transformers

26 citations · 32 across the 5 of their papers we have counts for

collaborators

9 papers

cs.GR2025

Generating Human-AI Collaborative Design Sequence for 3D Assets via Differentiable Operation Graph

Xiaoyang Huang, Bingbing Ni, Wenjun Zhang

The emergence of 3D artificial intelligence-generated content (3D-AIGC) has enabled rapid synthesis of intricate geometries. However, a fundamental disconnect persists between AI-g…

cs.CV2025

InstantSticker: Realistic Decal Blending via Disentangled Object Reconstruction

Yi Zhang, Xiaoyang Huang, Yishun Dou +5

We present InstantSticker, a disentangled reconstruction pipeline based on Image-Based Lighting (IBL), which focuses on highly realistic decal blending, simulates stickers attached…

cs.CV20223 cited

Boosting Point Clouds Rendering via Radiance Mapping

Xiaoyang Huang, Yi Zhang, Bingbing Ni +3

Recent years we have witnessed rapid development in NeRF-based image rendering due to its high quality. However, point clouds rendering is somehow less explored. Compared to NeRF-b…

cs.CV20223 cited

Representation-Agnostic Shape Fields

Xiaoyang Huang, Jiancheng Yang, Yanjun Wang +5

3D shape analysis has been widely explored in the era of deep learning. Numerous models have been developed for various 3D data representation formats, e.g., MeshCNN for meshes, Po…

cs.CR2020

Learning Black-Box Attackers with Transferable Priors and Query Feedback

Jiancheng Yang, Yangzhou Jiang, Xiaoyang Huang +2

This paper addresses the challenging black-box adversarial attack problem, where only classification confidence of a victim model is available. Inspired by consistency of visual sa…

cs.CV2020

AlignShift: Bridging the Gap of Imaging Thickness in 3D Anisotropic Volumes

Jiancheng Yang, Yi He, Xiaoyang Huang +4

This paper addresses a fundamental challenge in 3D medical image processing: how to deal with imaging thickness. For anisotropic medical volumes, there is a significant performance…