958 citations · 1.4k across the 9 of their papers we have counts for
11 papers
Learning to Factorize and Relight a City
Andrew Liu, Shiry Ginosar, Tinghui Zhou +2
We propose a learning-based framework for disentangling outdoor scenes into temporally-varying illumination and permanent scene factors. Inspired by the classic intrinsic image dec…
Exploring Simple and Transferable Recognition-Aware Image Processing
Zhuang Liu, Hung-Ju Wang, Tinghui Zhou +4
Recent progress in image recognition has stimulated the deployment of vision systems at an unprecedented scale. As a result, visual data are now often consumed not only by humans b…
Rethinking the Value of Network Pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou +2
Network pruning is widely used for reducing the heavy inference cost of deep models in low-resource settings. A typical pruning algorithm is a three-stage pipeline, i.e., training…
Everybody Dance Now
Caroline Chan, Shiry Ginosar, Tinghui Zhou +1
This paper presents a simple method for "do as I do" motion transfer: given a source video of a person dancing, we can transfer that performance to a novel (amateur) target after o…
Stereo Magnification: Learning View Synthesis using Multiplane Images
Tinghui Zhou, Richard Tucker, John Flynn +2
The view synthesis problem--generating novel views of a scene from known imagery--has garnered recent attention due in part to compelling applications in virtual and augmented real…
Multi-view Supervision for Single-view Reconstruction via Differentiable Ray Consistency
Shubham Tulsiani, Tinghui Zhou, Alexei A. Efros +1
We study the notion of consistency between a 3D shape and a 2D observation and propose a differentiable formulation which allows computing gradients of the 3D shape given an observ…
Unsupervised Learning of Depth and Ego-Motion from Video
Tinghui Zhou, Matthew Brown, Noah Snavely +1
We present an unsupervised learning framework for the task of monocular depth and camera motion estimation from unstructured video sequences. We achieve this by simultaneously trai…
Image-to-Image Translation with Conditional Adversarial Networks
Phillip Isola, Jun-Yan Zhu, Tinghui Zhou +1
We investigate conditional adversarial networks as a general-purpose solution to image-to-image translation problems. These networks not only learn the mapping from input image to…
View Synthesis by Appearance Flow
Tinghui Zhou, Shubham Tulsiani, Weilun Sun +2
We address the problem of novel view synthesis: given an input image, synthesizing new images of the same object or scene observed from arbitrary viewpoints. We approach this as a…
Learning Dense Correspondence via 3D-guided Cycle Consistency
Tinghui Zhou, Philipp Krähenbühl, Mathieu Aubry +2
Discriminative deep learning approaches have shown impressive results for problems where human-labeled ground truth is plentiful, but what about tasks where labels are difficult or…
Learning Data-driven Reflectance Priors for Intrinsic Image Decomposition
Tinghui Zhou, Philipp Krähenbühl, Alexei A. Efros
We propose a data-driven approach for intrinsic image decomposition, which is the process of inferring the confounding factors of reflectance and shading in an image. We pose this…