5 citations · 12 across the 9 of their papers we have counts for
9 papers · 1 filter
Ego-1K -- A Large-Scale Multiview Video Dataset for Egocentric Vision
Jae Yong Lee, Daniel Scharstein, Akash Bapat +11
We present Ego-1K, a large-scale collection of time-synchronized egocentric multiview videos designed to advance neural 3D video synthesis and dynamic scene understanding. The data…
Plenoptic PNG: Real-Time Neural Radiance Fields in 150 KB
Jae Yong Lee, Yuqun Wu, Chuhang Zou +2
The goal of this paper is to encode a 3D scene into an extremely compact representation from 2D images and to enable its transmittance, decoding and rendering in real-time across v…
MonoPatchNeRF: Improving Neural Radiance Fields with Patch-based Monocular Guidance
Yuqun Wu, Jae Yong Lee, Chuhang Zou +2
The latest regularized Neural Radiance Field (NeRF) approaches produce poor geometry and view extrapolation for large scale sparse view scenes, such as ETH3D. Density-based approac…
Region-Based Representations Revisited
Michal Shlapentokh-Rothman, Ansel Blume, Yao Xiao +7
We investigate whether region-based representations are effective for recognition. Regions were once a mainstay in recognition approaches, but pixel and patch-based features are no…
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…
DIVeR: Real-time and Accurate Neural Radiance Fields with Deterministic Integration for Volume Rendering
Liwen Wu, Jae Yong Lee, Anand Bhattad +2
DIVeR builds on the key ideas of NeRF and its variants -- density models and volume rendering -- to learn 3D object models that can be rendered realistically from small numbers of…
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…