Search Results for author: Shichen Liu

Found 16 papers, 6 papers with code

Exemplar-based Pattern Synthesis with Implicit Periodic Field Network

no code implementations4 Apr 2022 Haiwei Chen, Jiayi Liu, Weikai Chen, Shichen Liu, Yajie Zhao

In this paper, we propose an exemplar-based visual pattern synthesis framework that aims to model the inner statistics of visual patterns and generate new, versatile patterns that meet the aforementioned requirements.

Texture Synthesis

Topologically Consistent Multi-View Face Inference Using Volumetric Sampling

no code implementations ICCV 2021 Tianye Li, Shichen Liu, Timo Bolkart, Jiayi Liu, Hao Li, Yajie Zhao

We propose ToFu, Topologically consistent Face from multi-view, a geometry inference framework that can produce topologically consistent meshes across facial identities and expressions using a volumetric representation instead of an explicit underlying 3DMM.

3D Reconstruction

NeRD: Neural 3D Reflection Symmetry Detector

2 code implementations CVPR 2021 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.

Pose Estimation

Equivariant Point Network for 3D Point Cloud Analysis

1 code implementation CVPR 2021 Haiwei Chen, Shichen Liu, Weikai Chen, Hao Li

Features that are equivariant to a larger group of symmetries have been shown to be more discriminative and powerful in recent studies.

VaPiD: A Rapid Vanishing Point Detector via Learned Optimizers

no code implementations ICCV 2021 Shichen Liu, Yichao Zhou, Yajie Zhao

Being able to infer 3D structures from 2D images with geometric principles, vanishing points have been a well-recognized concept in 3D vision research.

Autonomous Driving Camera Calibration +1

Learning to Detect 3D Reflection Symmetry for Single-View Reconstruction

2 code implementations17 Jun 2020 Yichao Zhou, Shichen Liu, Yi Ma

In this work, we focus on object-level 3D reconstruction and present a geometry-based end-to-end deep learning framework that first detects the mirror plane of reflection symmetry that commonly exists in man-made objects and then predicts depth maps by finding the intra-image pixel-wise correspondence of the symmetry.

3D Reconstruction Single-View 3D Reconstruction

Learning to Infer Implicit Surfaces without 3D Supervision

no code implementations NeurIPS 2019 Shichen Liu, Shunsuke Saito, Weikai Chen, Hao Li

The representation of 3D surfaces itself is a key factor for the quality and resolution of the 3D output.

3D Shape Generation

Soft Rasterizer: Differentiable Rendering for Unsupervised Single-View Mesh Reconstruction

no code implementations17 Jan 2019 Shichen Liu, Weikai Chen, Tianye Li, Hao Li

We also show that our soft rasterizer can achieve comparable results to the cutting-edge supervised learning method and in various cases even better ones, especially for real-world data.

Learning to Collaborate: Multi-Scenario Ranking via Multi-Agent Reinforcement Learning

no code implementations17 Sep 2018 Jun Feng, Heng Li, Minlie Huang, Shichen Liu, Wenwu Ou, Zhirong Wang, Xiaoyan Zhu

The first one is lack of collaboration between scenarios meaning that each strategy maximizes its own objective but ignores the goals of other strategies, leading to a sub-optimal overall performance.

Multi-agent Reinforcement Learning reinforcement-learning

Perceive Your Users in Depth: Learning Universal User Representations from Multiple E-commerce Tasks

no code implementations28 May 2018 Yabo Ni, Dan Ou, Shichen Liu, Xiang Li, Wenwu Ou, An-Xiang Zeng, Luo Si

In this work, we propose to learn universal user representations across multiple tasks for more e ective personalization.

Deep Visual-Semantic Quantization for Efficient Image Retrieval

no code implementations CVPR 2017 Yue Cao, Mingsheng Long, Jian-Min Wang, Shichen Liu

This paper presents a compact coding solution with a focus on the deep learning to quantization approach, which improves retrieval quality by end-to-end representation learning and compact encoding and has already shown the superior performance over the hashing solutions for similarity retrieval.

Image Retrieval Quantization +1

Cascade Ranking for Operational E-commerce Search

no code implementations7 Jun 2017 Shichen Liu, Fei Xiao, Wenwu Ou, Luo Si

Real-world search applications often involve multiple factors of preferences or constraints with respect to user experience and computational costs such as search accuracy, search latency, size of search results and total CPU cost, while most existing search solutions only address one or two factors; 2).

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