Search Results for author: Guandao Yang

Found 11 papers, 9 papers with code

Residual Aligned: Gradient Optimization for Non-Negative Image Synthesis

no code implementations8 Feb 2022 Flora Yu Shen, Katie Luo, Guandao Yang, Harald Haraldsson, Serge Belongie

In this work, we address an important problem of optical see through (OST) augmented reality: non-negative image synthesis.

Image-to-Image Translation Translation

Stay Positive: Non-Negative Image Synthesis for Augmented Reality

1 code implementation CVPR 2021 Katie Luo, Guandao Yang, Wenqi Xian, Harald Haraldsson, Bharath Hariharan, Serge Belongie

In applications such as optical see-through and projector augmented reality, producing images amounts to solving non-negative image generation, where one can only add light to an existing image.

Image-to-Image Translation Style Transfer

Geometry Processing with Neural Fields

1 code implementation NeurIPS 2021 Guandao Yang, Serge Belongie, Bharath Hariharan, Vladlen Koltun

Most existing geometry processing algorithms use meshes as the default shape representation.

QPyTorch: A Low-Precision Arithmetic Simulation Framework

2 code implementations9 Oct 2019 Tianyi Zhang, Zhiqiu Lin, Guandao Yang, Christopher De Sa

Low-precision training reduces computational cost and produces efficient models.


PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows

11 code implementations ICCV 2019 Guandao Yang, Xun Huang, Zekun Hao, Ming-Yu Liu, Serge Belongie, Bharath Hariharan

Specifically, we learn a two-level hierarchy of distributions where the first level is the distribution of shapes and the second level is the distribution of points given a shape.

Point Cloud Generation Variational Inference

SWALP : Stochastic Weight Averaging in Low-Precision Training

2 code implementations26 Apr 2019 Guandao Yang, Tianyi Zhang, Polina Kirichenko, Junwen Bai, Andrew Gordon Wilson, Christopher De Sa

Low precision operations can provide scalability, memory savings, portability, and energy efficiency.

Learning to Evaluate Image Captioning

1 code implementation CVPR 2018 Yin Cui, Guandao Yang, Andreas Veit, Xun Huang, Serge Belongie

To address these two challenges, we propose a novel learning based discriminative evaluation metric that is directly trained to distinguish between human and machine-generated captions.

Data Augmentation Image Captioning

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