papers

Publications (25)

cs.CV2021

NeRD: Neural 3D Reflection Symmetry Detector

Yichao Zhou, Shichen Liu, Yi Ma

Recent advances have shown that symmetry, a structural prior that most objects exhibit, can support a variety of single-view 3D understanding tasks. However, detecting 3D symmetry…

cs.CV2026

Archon: A Unified Multimodal Model for Holistic Digital Human Generation

Chong Bao, Shichen Liu, Lijun Yu +9

Digital humans are fundamental to immersive interaction, yet creating a unified model for holistic modalities, including text, audio, motion, and visual content, remains an open ch…

cs.CV2019

Learning to Infer Implicit Surfaces without 3D Supervision

Shichen Liu, Shunsuke Saito, Weikai Chen +1

Recent advances in 3D deep learning have shown that it is possible to train highly effective deep models for 3D shape generation, directly from 2D images. This is particularly inte…

cs.CV2018

CondenseNet: An Efficient DenseNet using Learned Group Convolutions

Gao Huang, Shichen Liu, Laurens van der Maaten +1

Deep neural networks are increasingly used on mobile devices, where computational resources are limited. In this paper we develop CondenseNet, a novel network architecture with unp…

cs.CV2026

Talking Together: Synthesizing Co-Located 3D Conversations from Audio

Mengyi Shan, Shouchieh Chang, Ziqian Bai +6

We tackle the challenging task of generating complete 3D facial animations for two interacting, co-located participants from a mixed audio stream. While existing methods often prod…

cs.CV2021

HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures

Yichao Zhou, Jingwei Huang, Xili Dai +4

We present HoliCity, a city-scale 3D dataset with rich structural information. Currently, this dataset has 6,300 real-world panoramas of resolution that are acc…