115 citations · 196 across the 11 of their papers we have counts for
31 papers · 1 filter
NeRFiller: Completing Scenes via Generative 3D Inpainting
Ethan Weber, Aleksander Hołyński, Varun Jampani +4
We propose NeRFiller, an approach that completes missing portions of a 3D capture via generative 3D inpainting using off-the-shelf 2D visual generative models. Often parts of a cap…
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…
Discovering 3D Parts from Image Collections
Chun-Han Yao, Wei-Chih Hung, Varun Jampani +1
Reasoning 3D shapes from 2D images is an essential yet challenging task, especially when only single-view images are at our disposal. While an object can have a complicated shape,…
Adaptive Prototype Learning and Allocation for Few-Shot Segmentation
Gen Li, Varun Jampani, Laura Sevilla-Lara +3
Prototype learning is extensively used for few-shot segmentation. Typically, a single prototype is obtained from the support feature by averaging the global object information. How…
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…
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…