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Found 13 papers, 8 papers with code
Virtual Occlusions Through Implicit Depth
We instead propose an implicit model for depth and use that to predict the occlusion mask directly.
Removing Objects From Neural Radiance Fields
We validate our approach using a new and still-challenging dataset for the task of NeRF inpainting.
SimpleRecon: 3D Reconstruction Without 3D Convolutions
Traditionally, 3D indoor scene reconstruction from posed images happens in two phases: per-image depth estimation, followed by depth merging and surface reconstruction.
Single Image Depth Prediction with Wavelet Decomposition
We present a novel method for predicting accurate depths from monocular images with high efficiency.
The Temporal Opportunist: Self-Supervised Multi-Frame Monocular Depth
We propose ManyDepth, an adaptive approach to dense depth estimation that can make use of sequence information at test time, when it is available.
Monocular Depth Estimation
Unsupervised Monocular Depth Estimation
Panoptic Segmentation Forecasting
Following this decomposition, we introduce panoptic segmentation forecasting.
DiverseNet: When One Right Answer is not Enough
For a single input, we learn to predict a range of possible answers.
Learning Stereo from Single Images
We propose that it is unnecessary to have such a high reliance on ground truth depths or even corresponding stereo pairs.
Footprints and Free Space from a Single Color Image
We introduce a model to predict the geometry of both visible and occluded traversable surfaces, given a single RGB image as input.
Self-Supervised Monocular Depth Hints
Monocular depth estimators can be trained with various forms of self-supervision from binocular-stereo data to circumvent the need for high-quality laser scans or other ground-truth data.
Ranked #2 on
Monocular Depth Estimation
on VA (Virtual Apartment)
Digging Into Self-Supervised Monocular Depth Estimation
Per-pixel ground-truth depth data is challenging to acquire at scale.
Ranked #3 on
Monocular Depth Estimation
on VA (Virtual Apartment)
Structured Prediction of Unobserved Voxels From a Single Depth Image
Building a complete 3D model of a scene, given only a single depth image, is underconstrained.
RGBD Datasets: Past, Present and Future
Since the launch of the Microsoft Kinect, scores of RGBD datasets have been released.
