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20192024
most citedDepth Extraction from Video Using Non-parametric Sampling

274 citations · 325 across the 7 of their papers we have counts for

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9 papers · 1 filter

cs.CV20223 cited

MaskGIT: Masked Generative Image Transformer

Huiwen Chang, Han Zhang, Lu Jiang +2

Generative transformers have experienced rapid popularity growth in the computer vision community in synthesizing high-fidelity and high-resolution images. The best generative tran…

cs.CV202119 cited

Neural-PIL: Neural Pre-Integrated Lighting for Reflectance Decomposition

Mark Boss, Varun Jampani, Raphael Braun +3

Decomposing a scene into its shape, reflectance and illumination is a fundamental problem in computer vision and graphics. Neural approaches such as NeRF have achieved remarkable s…

cs.CV20212 cited

SLIDE: Single Image 3D Photography with Soft Layering and Depth-aware Inpainting

Varun Jampani, Huiwen Chang, Kyle Sargent +8

Single image 3D photography enables viewers to view a still image from novel viewpoints. Recent approaches combine monocular depth networks with inpainting networks to achieve comp…

cs.CV2021

LASR: Learning Articulated Shape Reconstruction from a Monocular Video

Gengshan Yang, Deqing Sun, Varun Jampani +6

Remarkable progress has been made in 3D reconstruction of rigid structures from a video or a collection of images. However, it is still challenging to reconstruct nonrigid structur…

cs.CV2021

COMISR: Compression-Informed Video Super-Resolution

Yinxiao Li, Pengchong Jin, Feng Yang +3

Most video super-resolution methods focus on restoring high-resolution video frames from low-resolution videos without taking into account compression. However, most videos on the…

cs.CV2021

AutoFlow: Learning a Better Training Set for Optical Flow

Deqing Sun, Daniel Vlasic, Charles Herrmann +6

Synthetic datasets play a critical role in pre-training CNN models for optical flow, but they are painstaking to generate and hard to adapt to new applications. To automate the pro…