Search Results for author: Oliver Wang

Found 50 papers, 29 papers with code

LandscapeAR: Large Scale Outdoor Augmented Reality by Matching Photographs with Terrain Models Using Learned Descriptors

1 code implementation ECCV 2020 Jan Brejcha, Michal Lukáč, Yannick Hold-Geoffroy, Oliver Wang, Martin Čadík

We introduce a solution to large scale Augmented Reality for outdoor scenes by registering camera images to textured Digital Elevation Models (DEMs).

Ranked #2 on Patch Matching on HPatches (using extra training data)

Patch Matching

INVE: Interactive Neural Video Editing

no code implementations15 Jul 2023 Jiahui Huang, Leonid Sigal, Kwang Moo Yi, Oliver Wang, Joon-Young Lee

We present Interactive Neural Video Editing (INVE), a real-time video editing solution, which can assist the video editing process by consistently propagating sparse frame edits to the entire video clip.

Video Editing

3inGAN: Learning a 3D Generative Model from Images of a Self-similar Scene

no code implementations27 Nov 2022 Animesh Karnewar, Oliver Wang, Tobias Ritschel, Niloy Mitra

We introduce 3inGAN, an unconditional 3D generative model trained from 2D images of a single self-similar 3D scene.

Towards Accurate Reconstruction of 3D Scene Shape from A Single Monocular Image

1 code implementation28 Aug 2022 Wei Yin, Jianming Zhang, Oliver Wang, Simon Niklaus, Simon Chen, Yifan Liu, Chunhua Shen

To do so, we propose a two-stage framework that first predicts depth up to an unknown scale and shift from a single monocular image, and then exploits 3D point cloud data to predict the depth shift and the camera's focal length that allow us to recover 3D scene shapes.

Depth Estimation Depth Prediction

Towards Domain-agnostic Depth Completion

1 code implementation29 Jul 2022 Wei Yin, Jianming Zhang, Oliver Wang, Simon Niklaus, Simon Chen, Chunhua Shen

Our method leverages a data driven prior in the form of a single image depth prediction network trained on large-scale datasets, the output of which is used as an input to our model.

Depth Completion Depth Estimation +2

Neural Volumetric Object Selection

no code implementations CVPR 2022 Zhongzheng Ren, Aseem Agarwala, Bryan Russell, Alexander G. Schwing, Oliver Wang

We introduce an approach for selecting objects in neural volumetric 3D representations, such as multi-plane images (MPI) and neural radiance fields (NeRF).

ReLU Fields: The Little Non-linearity That Could

no code implementations22 May 2022 Animesh Karnewar, Tobias Ritschel, Oliver Wang, Niloy J. Mitra

Although the MLPs are able to represent complex scenes with unprecedented quality and memory footprint, this expressive power of the MLPs, however, comes at the cost of long training and inference times.

Layered Neural Atlases for Consistent Video Editing

2 code implementations23 Sep 2021 Yoni Kasten, Dolev Ofri, Oliver Wang, Tali Dekel

We present a method that decomposes, or "unwraps", an input video into a set of layered 2D atlases, each providing a unified representation of the appearance of an object (or background) over the video.

Style Transfer Video Editing +2

GaussiGAN: Controllable Image Synthesis with 3D Gaussians from Unposed Silhouettes

no code implementations24 Jun 2021 Youssef A. Mejjati, Isa Milefchik, Aaron Gokaslan, Oliver Wang, Kwang In Kim, James Tompkin

We present an algorithm that learns a coarse 3D representation of objects from unposed multi-view 2D mask supervision, then uses it to generate detailed mask and image texture.

Image Generation Object Reconstruction

Differentiable Signal Processing With Black-Box Audio Effects

2 code implementations11 May 2021 Marco A. Martínez Ramírez, Oliver Wang, Paris Smaragdis, Nicholas J. Bryan

We present a data-driven approach to automate audio signal processing by incorporating stateful third-party, audio effects as layers within a deep neural network.

Audio Signal Processing

Sampling Based Scene-Space Video Processing

no code implementations5 Feb 2021 Felix Klose, Oliver Wang, Jean-Charles Bazin, Marcus Magnor, Alexander Sorkine-Hornung

We present a novel, sampling-based framework for processing video that enables high-quality scene-space video effects in the presence of inevitable errors in depth and camera pose estimation.

Deblurring Denoising +2

CharacterGAN: Few-Shot Keypoint Character Animation and Reposing

1 code implementation5 Feb 2021 Tobias Hinz, Matthew Fisher, Oliver Wang, Eli Shechtman, Stefan Wermter

Our model generates novel poses based on keypoint locations, which can be modified in real time while providing interactive feedback, allowing for intuitive reposing and animation.

DuctTake: Spatiotemporal Video Compositing

no code implementations12 Jan 2021 Jan Rueegg, Oliver Wang, Aljoscha Smolic, Markus Gross

DuctTake is a system designed to enable practical compositing of multiple takes of a scene into a single video.

Semantic Segmentation

Learning to Recover 3D Scene Shape from a Single Image

1 code implementation CVPR 2021 Wei Yin, Jianming Zhang, Oliver Wang, Simon Niklaus, Long Mai, Simon Chen, Chunhua Shen

Despite significant progress in monocular depth estimation in the wild, recent state-of-the-art methods cannot be used to recover accurate 3D scene shape due to an unknown depth shift induced by shift-invariant reconstruction losses used in mixed-data depth prediction training, and possible unknown camera focal length.

 Ranked #1 on Indoor Monocular Depth Estimation on DIODE (using extra training data)

3D Scene Reconstruction Depth Prediction +3

Neural Scene Flow Fields for Space-Time View Synthesis of Dynamic Scenes

3 code implementations CVPR 2021 Zhengqi Li, Simon Niklaus, Noah Snavely, Oliver Wang

We present a method to perform novel view and time synthesis of dynamic scenes, requiring only a monocular video with known camera poses as input.

Revisiting Adaptive Convolutions for Video Frame Interpolation

no code implementations2 Nov 2020 Simon Niklaus, Long Mai, Oliver Wang

Video frame interpolation, the synthesis of novel views in time, is an increasingly popular research direction with many new papers further advancing the state of the art.

Image Denoising Video Frame Interpolation +1

Real-time Semantic Segmentation with Fast Attention

1 code implementation7 Jul 2020 Ping Hu, Federico Perazzi, Fabian Caba Heilbron, Oliver Wang, Zhe Lin, Kate Saenko, Stan Sclaroff

The proposed architecture relies on our fast spatial attention, which is a simple yet efficient modification of the popular self-attention mechanism and captures the same rich spatial context at a small fraction of the computational cost, by changing the order of operations.

Real-Time Semantic Segmentation

Swapping Autoencoder for Deep Image Manipulation

4 code implementations NeurIPS 2020 Taesung Park, Jun-Yan Zhu, Oliver Wang, Jingwan Lu, Eli Shechtman, Alexei A. Efros, Richard Zhang

Deep generative models have become increasingly effective at producing realistic images from randomly sampled seeds, but using such models for controllable manipulation of existing images remains challenging.

Image Manipulation

Improved Techniques for Training Single-Image GANs

3 code implementations25 Mar 2020 Tobias Hinz, Matthew Fisher, Oliver Wang, Stefan Wermter

Recently there has been an interest in the potential of learning generative models from a single image, as opposed to from a large dataset.

Image Generation single-image-generation

Generating Object Stamps

1 code implementation1 Jan 2020 Youssef Alami Mejjati, Zejiang Shen, Michael Snower, Aaron Gokaslan, Oliver Wang, James Tompkin, Kwang In Kim

We present an algorithm to generate diverse foreground objects and composite them into background images using a GAN architecture.

CNN-generated images are surprisingly easy to spot... for now

4 code implementations CVPR 2020 Sheng-Yu Wang, Oliver Wang, Richard Zhang, Andrew Owens, Alexei A. Efros

In this work we ask whether it is possible to create a "universal" detector for telling apart real images from these generated by a CNN, regardless of architecture or dataset used.

Data Augmentation Image Generation +1

Detecting Photoshopped Faces by Scripting Photoshop

2 code implementations ICCV 2019 Sheng-Yu Wang, Oliver Wang, Andrew Owens, Richard Zhang, Alexei A. Efros

Most malicious photo manipulations are created using standard image editing tools, such as Adobe Photoshop.

Image Manipulation Detection

Web Stereo Video Supervision for Depth Prediction from Dynamic Scenes

no code implementations25 Apr 2019 Chaoyang Wang, Simon Lucey, Federico Perazzi, Oliver Wang

We present a fully data-driven method to compute depth from diverse monocular video sequences that contain large amounts of non-rigid objects, e. g., people.

Depth Estimation Depth Prediction

MSG-GAN: Multi-Scale Gradients for Generative Adversarial Networks

4 code implementations CVPR 2020 Animesh Karnewar, Oliver Wang

While Generative Adversarial Networks (GANs) have seen huge successes in image synthesis tasks, they are notoriously difficult to adapt to different datasets, in part due to instability during training and sensitivity to hyperparameters.

Image Generation

B-Script: Transcript-based B-roll Video Editing with Recommendations

no code implementations28 Feb 2019 Bernd Huber, Hijung Valentina Shin, Bryan Russell, Oliver Wang, Gautham J. Mysore

In video production, inserting B-roll is a widely used technique to enrich the story and make a video more engaging.

Video Editing

Self-Supervised Generation of Spatial Audio for 360° Video

no code implementations NeurIPS 2018 Pedro Morgado, Nuno Nvasconcelos, Timothy Langlois, Oliver Wang

We introduce an approach to convert mono audio recorded by a 360° video camera into spatial audio, a representation of the distribution of sound over the full viewing sphere.

DeepLens: Shallow Depth Of Field From A Single Image

no code implementations18 Oct 2018 Lijun Wang, Xiaohui Shen, Jianming Zhang, Oliver Wang, Zhe Lin, Chih-Yao Hsieh, Sarah Kong, Huchuan Lu

To achieve this, we propose a novel neural network model comprised of a depth prediction module, a lens blur module, and a guided upsampling module.

Depth Estimation Depth Prediction

Self-Supervised Generation of Spatial Audio for 360 Video

1 code implementation7 Sep 2018 Pedro Morgado, Nuno Vasconcelos, Timothy Langlois, Oliver Wang

Using our approach, we show that it is possible to infer the spatial location of sound sources based only on 360 video and a mono audio track.

Localizing Moments in Video with Temporal Language

1 code implementation EMNLP 2018 Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, Bryan Russell

To benchmark whether our model, and other recent video localization models, can effectively reason about temporal language, we collect the novel TEMPOral reasoning in video and language (TEMPO) dataset.

Natural Language Queries Retrieval +1

Learning Blind Video Temporal Consistency

1 code implementation ECCV 2018 Wei-Sheng Lai, Jia-Bin Huang, Oliver Wang, Eli Shechtman, Ersin Yumer, Ming-Hsuan Yang

Our method takes the original unprocessed and per-frame processed videos as inputs to produce a temporally consistent video.

Colorization Image-to-Image Translation +4

ST-GAN: Spatial Transformer Generative Adversarial Networks for Image Compositing

2 code implementations CVPR 2018 Chen-Hsuan Lin, Ersin Yumer, Oliver Wang, Eli Shechtman, Simon Lucey

We address the problem of finding realistic geometric corrections to a foreground object such that it appears natural when composited into a background image.

GSLAM: Initialization-robust Monocular Visual SLAM via Global Structure-from-Motion

no code implementations16 Aug 2017 Chengzhou Tang, Oliver Wang, Ping Tan

Many monocular visual SLAM algorithms are derived from incremental structure-from-motion (SfM) methods.

Visual Odometry

Localizing Moments in Video with Natural Language

2 code implementations ICCV 2017 Lisa Anne Hendricks, Oliver Wang, Eli Shechtman, Josef Sivic, Trevor Darrell, Bryan Russell

A key obstacle to training our MCN model is that current video datasets do not include pairs of localized video segments and referring expressions, or text descriptions which uniquely identify a corresponding moment.

Natural Language Queries

Deep Video Deblurring for Hand-Held Cameras

1 code implementation CVPR 2017 Shuochen Su, Mauricio Delbracio, Jue Wang, Guillermo Sapiro, Wolfgang Heidrich, Oliver Wang

We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

Deblurring Image Deblurring +1

Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

1 code implementation CVPR 2016 Patrick Wieschollek, Oliver Wang, Alexander Sorkine-Hornung, Hendrik P. A. Lensch

We present a new approach for efficient approximate nearest neighbor (ANN) search in high dimensional spaces, extending the idea of Product Quantization.

Quantization Re-Ranking

High-Resolution Image Inpainting using Multi-Scale Neural Patch Synthesis

1 code implementation CVPR 2017 Chao Yang, Xin Lu, Zhe Lin, Eli Shechtman, Oliver Wang, Hao Li

Recent advances in deep learning have shown exciting promise in filling large holes in natural images with semantically plausible and context aware details, impacting fundamental image manipulation tasks such as object removal.

Image Inpainting Image Manipulation +1

Deep Video Deblurring

1 code implementation25 Nov 2016 Shuochen Su, Mauricio Delbracio, Jue Wang, Guillermo Sapiro, Wolfgang Heidrich, Oliver Wang

We show that the features learned from this dataset extend to deblurring motion blur that arises due to camera shake in a wide range of videos, and compare the quality of results to a number of other baselines.

Deblurring Image Deblurring +1

Scalable Structure From Motion for Densely Sampled Videos

no code implementations CVPR 2015 Benjamin Resch, Hendrik P. A. Lensch, Oliver Wang, Marc Pollefeys, Alexander Sorkine-Hornung

Videos consisting of thousands of high resolution frames are challenging for existing structure from motion (SfM) and simultaneous-localization and mapping (SLAM) techniques.

Pose Estimation Simultaneous Localization and Mapping

Phase-Based Frame Interpolation for Video

no code implementations CVPR 2015 Simone Meyer, Oliver Wang, Henning Zimmer, Max Grosse, Alexander Sorkine-Hornung

Standard approaches to computing interpolated (in-between) frames in a video sequence require accurate pixel correspondences between images e. g. using optical flow.

Image Generation Optical Flow Estimation

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