Search Results for author: Zaiwei Zhang

Found 7 papers, 6 papers with code

Scene Synthesis via Uncertainty-Driven Attribute Synchronization

1 code implementation ICCV 2021 Haitao Yang, Zaiwei Zhang, Siming Yan, Haibin Huang, Chongyang Ma, Yi Zheng, Chandrajit Bajaj, QiXing Huang

This task is challenging because 3D scenes exhibit diverse patterns, ranging from continuous ones, such as object sizes and the relative poses between pairs of shapes, to discrete patterns, such as occurrence and co-occurrence of objects with symmetrical relationships.

Self-Supervised Pretraining of 3D Features on any Point-Cloud

1 code implementation ICCV 2021 Zaiwei Zhang, Rohit Girdhar, Armand Joulin, Ishan Misra

Pretraining on large labeled datasets is a prerequisite to achieve good performance in many computer vision tasks like 2D object recognition, video classification etc.

Object Detection Object Recognition +2

H3DNet: 3D Object Detection Using Hybrid Geometric Primitives

2 code implementations ECCV 2020 Zaiwei Zhang, Bo Sun, Haitao Yang, Qi-Xing Huang

We show how to convert the predicted geometric primitives into object proposals by defining a distance function between an object and the geometric primitives.

3D Object Detection

Joint Learning of Neural Networks via Iterative Reweighted Least Squares

1 code implementation16 May 2019 Zaiwei Zhang, Xiangru Huang, Qi-Xing Huang, Xiao Zhang, Yuan Li

We formulate this problem as joint learning of multiple copies of the same network architecture and enforce the network weights to be shared across these networks.

General Classification Image Classification +1

Path-Invariant Map Networks

1 code implementation CVPR 2019 Zaiwei Zhang, Zhenxiao Liang, Lemeng Wu, Xiaowei Zhou, Qi-Xing Huang

Optimizing a network of maps among a collection of objects/domains (or map synchronization) is a central problem across computer vision and many other relevant fields.

3D Semantic Segmentation Scene Segmentation

Deep Generative Modeling for Scene Synthesis via Hybrid Representations

no code implementations6 Aug 2018 Zaiwei Zhang, Zhenpei Yang, Chongyang Ma, Linjie Luo, Alexander Huth, Etienne Vouga, Qi-Xing Huang

We show a principled way to train this model by combining discriminator losses for both a 3D object arrangement representation and a 2D image-based representation.

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