22 citations · 39 across the 7 of their papers we have counts for
22 papers
Sparse SPN: Depth Completion from Sparse Keypoints
Yuqun Wu, Jae Yong Lee, Derek Hoiem
Our long term goal is to use image-based depth completion to quickly create 3D models from sparse point clouds, e.g. from SfM or SLAM. Much progress has been made in depth completi…
QFF: Quantized Fourier Features for Neural Field Representations
Jae Yong Lee, Yuqun Wu, Chuhang Zou +2
Multilayer perceptrons (MLPs) learn high frequencies slowly. Recent approaches encode features in spatial bins to improve speed of learning details, but at the cost of larger model…
Deep PatchMatch MVS with Learned Patch Coplanarity, Geometric Consistency and Adaptive Pixel Sampling
Jae Yong Lee, Chuhang Zou, Derek Hoiem
Recent work in multi-view stereo (MVS) combines learnable photometric scores and regularization with PatchMatch-based optimization to achieve robust pixelwise estimates of depth, n…
GRIT: General Robust Image Task Benchmark
Tanmay Gupta, Ryan Marten, Aniruddha Kembhavi +1
Computer vision models excel at making predictions when the test distribution closely resembles the training distribution. Such models have yet to match the ability of biological v…
PatchMatch-RL: Deep MVS with Pixelwise Depth, Normal, and Visibility
Jae Yong Lee, Joseph DeGol, Chuhang Zou +1
Recent learning-based multi-view stereo (MVS) methods show excellent performance with dense cameras and small depth ranges. However, non-learning based approaches still outperform…
Learning Curves for Analysis of Deep Networks
Derek Hoiem, Tanmay Gupta, Zhizhong Li +1
Learning curves model a classifier's test error as a function of the number of training samples. Prior works show that learning curves can be used to select model parameters and ex…