24 citations · 63 across the 6 of their papers we have counts for
6 papers · 1 filter
Residual Aligned: Gradient Optimization for Non-Negative Image Synthesis
Flora Yu Shen, Katie Luo, Guandao Yang +2
In this work, we address an important problem of optical see through (OST) augmented reality: non-negative image synthesis. Most of the image generation methods fail under this con…
Stay Positive: Non-Negative Image Synthesis for Augmented Reality
Katie Luo, Guandao Yang, Wenqi Xian +3
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 e…
Learning Gradient Fields for Shape Generation
Ruojin Cai, Guandao Yang, Hadar Averbuch-Elor +4
In this work, we propose a novel technique to generate shapes from point cloud data. A point cloud can be viewed as samples from a distribution of 3D points whose density is concen…
PointFlow: 3D Point Cloud Generation with Continuous Normalizing Flows
Guandao Yang, Xun Huang, Zekun Hao +3
As 3D point clouds become the representation of choice for multiple vision and graphics applications, the ability to synthesize or reconstruct high-resolution, high-fidelity point…
Deep Fundamental Matrix Estimation without Correspondences
Omid Poursaeed, Guandao Yang, Aditya Prakash +4
Estimating fundamental matrices is a classic problem in computer vision. Traditional methods rely heavily on the correctness of estimated key-point correspondences, which can be no…
Learning to Evaluate Image Captioning
Yin Cui, Guandao Yang, Andreas Veit +2
Evaluation metrics for image captioning face two challenges. Firstly, commonly used metrics such as CIDEr, METEOR, ROUGE and BLEU often do not correlate well with human judgments.…