Search Results for author: Deqing Sun

Found 53 papers, 25 papers with code

SAMPLING: Scene-adaptive Hierarchical Multiplane Images Representation for Novel View Synthesis from a Single Image

no code implementations12 Sep 2023 Xiaoyu Zhou, Zhiwei Lin, Xiaojun Shan, Yongtao Wang, Deqing Sun, Ming-Hsuan Yang

Recent novel view synthesis methods obtain promising results for relatively small scenes, e. g., indoor environments and scenes with a few objects, but tend to fail for unbounded outdoor scenes with a single image as input.

Novel View Synthesis

Substance or Style: What Does Your Image Embedding Know?

no code implementations10 Jul 2023 Cyrus Rashtchian, Charles Herrmann, Chun-Sung Ferng, Ayan Chakrabarti, Dilip Krishnan, Deqing Sun, Da-Cheng Juan, Andrew Tomkins

We find that image-text models (CLIP and ALIGN) are better at recognizing new examples of style transfer than masking-based models (CAN and MAE).

Style Transfer

ContactArt: Learning 3D Interaction Priors for Category-level Articulated Object and Hand Poses Estimation

no code implementations2 May 2023 Zehao Zhu, Jiashun Wang, Yuzhe Qin, Deqing Sun, Varun Jampani, Xiaolong Wang

We propose a new dataset and a novel approach to learning hand-object interaction priors for hand and articulated object pose estimation.

Hand Pose Estimation

LOCATE: Localize and Transfer Object Parts for Weakly Supervised Affordance Grounding

no code implementations CVPR 2023 Gen Li, Varun Jampani, Deqing Sun, Laura Sevilla-Lara

A key step to acquire this skill is to identify what part of the object affords each action, which is called affordance grounding.

VQ3D: Learning a 3D-Aware Generative Model on ImageNet

no code implementations14 Feb 2023 Kyle Sargent, Jing Yu Koh, Han Zhang, Huiwen Chang, Charles Herrmann, Pratul Srinivasan, Jiajun Wu, Deqing Sun

Recent work has shown the possibility of training generative models of 3D content from 2D image collections on small datasets corresponding to a single object class, such as human faces, animal faces, or cars.

Self-supervised AutoFlow

no code implementations CVPR 2023 Hsin-Ping Huang, Charles Herrmann, Junhwa Hur, Erika Lu, Kyle Sargent, Austin Stone, Ming-Hsuan Yang, Deqing Sun

Recently, AutoFlow has shown promising results on learning a training set for optical flow, but requires ground truth labels in the target domain to compute its search metric.

Optical Flow Estimation

Face Deblurring using Dual Camera Fusion on Mobile Phones

no code implementations23 Jul 2022 Wei-Sheng Lai, YiChang Shih, Lun-Cheng Chu, Xiaotong Wu, Sung-Fang Tsai, Michael Krainin, Deqing Sun, Chia-Kai Liang

To the best of our knowledge, our work is the first mobile solution for face motion deblurring that works reliably and robustly over thousands of images in diverse motion and lighting conditions.

Deblurring Image Deblurring

Adaptive Transformers for Robust Few-shot Cross-domain Face Anti-spoofing

no code implementations23 Mar 2022 Hsin-Ping Huang, Deqing Sun, Yaojie Liu, Wen-Sheng Chu, Taihong Xiao, Jinwei Yuan, Hartwig Adam, Ming-Hsuan Yang

While recent face anti-spoofing methods perform well under the intra-domain setups, an effective approach needs to account for much larger appearance variations of images acquired in complex scenes with different sensors for robust performance.

Face Anti-Spoofing

Disentangling Architecture and Training for Optical Flow

no code implementations21 Mar 2022 Deqing Sun, Charles Herrmann, Fitsum Reda, Michael Rubinstein, David Fleet, William T. Freeman

Our newly trained RAFT achieves an Fl-all score of 4. 31% on KITTI 2015, more accurate than all published optical flow methods at the time of writing.

Optical Flow Estimation

FILM: Frame Interpolation for Large Motion

2 code implementations10 Feb 2022 Fitsum Reda, Janne Kontkanen, Eric Tabellion, Deqing Sun, Caroline Pantofaru, Brian Curless

Recent methods use multiple networks to estimate optical flow or depth and a separate network dedicated to frame synthesis.

Optical Flow Estimation Video Frame Interpolation

ViSER: Video-Specific Surface Embeddings for Articulated 3D Shape Reconstruction

1 code implementation NeurIPS 2021 Gengshan Yang, Deqing Sun, Varun Jampani, Daniel Vlasic, Forrester Cole, Ce Liu, Deva Ramanan

The surface embeddings are implemented as coordinate-based MLPs that are fit to each video via consistency and contrastive reconstruction losses. Experimental results show that ViSER compares favorably against prior work on challenging videos of humans with loose clothing and unusual poses as well as animals videos from DAVIS and YTVOS.

3D Shape Reconstruction from Videos

Pyramid Adversarial Training Improves ViT Performance

1 code implementation CVPR 2022 Charles Herrmann, Kyle Sargent, Lu Jiang, Ramin Zabih, Huiwen Chang, Ce Liu, Dilip Krishnan, Deqing Sun

In this work, we present pyramid adversarial training (PyramidAT), a simple and effective technique to improve ViT's overall performance.

Ranked #6 on Domain Generalization on ImageNet-C (using extra training data)

Adversarial Attack Data Augmentation +2

AutoFlow: Learning a Better Training Set for Optical Flow

1 code implementation CVPR 2021 Deqing Sun, Daniel Vlasic, Charles Herrmann, Varun Jampani, Michael Krainin, Huiwen Chang, Ramin Zabih, William T. Freeman, Ce Liu

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.

Optical Flow Estimation

Adaptive Prototype Learning and Allocation for Few-Shot Segmentation

2 code implementations CVPR 2021 Gen Li, Varun Jampani, Laura Sevilla-Lara, Deqing Sun, Jonghyun Kim, Joongkyu Kim

By integrating the SGC and GPA together, we propose the Adaptive Superpixel-guided Network (ASGNet), which is a lightweight model and adapts to object scale and shape variation.

Clustering Few-Shot Semantic Segmentation

HumanGPS: Geodesic PreServing Feature for Dense Human Correspondences

1 code implementation CVPR 2021 Feitong Tan, Danhang Tang, Mingsong Dou, Kaiwen Guo, Rohit Pandey, Cem Keskin, Ruofei Du, Deqing Sun, Sofien Bouaziz, Sean Fanello, Ping Tan, yinda zhang

In this paper, we address the problem of building dense correspondences between human images under arbitrary camera viewpoints and body poses.

Improving Deep Stereo Network Generalization with Geometric Priors

no code implementations25 Aug 2020 Jialiang Wang, Varun Jampani, Deqing Sun, Charles Loop, Stan Birchfield, Jan Kautz

End-to-end deep learning methods have advanced stereo vision in recent years and obtained excellent results when the training and test data are similar.

Learnable Cost Volume Using the Cayley Representation

1 code implementation ECCV 2020 Taihong Xiao, Jinwei Yuan, Deqing Sun, Qifei Wang, Xin-Yu Zhang, Kehan Xu, Ming-Hsuan Yang

Cost volume is an essential component of recent deep models for optical flow estimation and is usually constructed by calculating the inner product between two feature vectors.

Optical Flow Estimation

Hierarchical Contrastive Motion Learning for Video Action Recognition

no code implementations20 Jul 2020 Xitong Yang, Xiaodong Yang, Sifei Liu, Deqing Sun, Larry Davis, Jan Kautz

Thus, the motion features at higher levels are trained to gradually capture semantic dynamics and evolve more discriminative for action recognition.

Action Recognition Contrastive Learning +2

SENSE: a Shared Encoder Network for Scene-flow Estimation

1 code implementation ICCV 2019 Huaizu Jiang, Deqing Sun, Varun Jampani, Zhaoyang Lv, Erik Learned-Miller, Jan Kautz

We introduce a compact network for holistic scene flow estimation, called SENSE, which shares common encoder features among four closely-related tasks: optical flow estimation, disparity estimation from stereo, occlusion estimation, and semantic segmentation.

Disparity Estimation Occlusion Estimation +3

Image Formation Model Guided Deep Image Super-Resolution

1 code implementation18 Aug 2019 Jinshan Pan, Yang Liu, Deqing Sun, Jimmy Ren, Ming-Ming Cheng, Jian Yang, Jinhui Tang

We present a simple and effective image super-resolution algorithm that imposes an image formation constraint on the deep neural networks via pixel substitution.

Image Super-Resolution

Video Stitching for Linear Camera Arrays

no code implementations31 Jul 2019 Wei-Sheng Lai, Orazio Gallo, Jinwei Gu, Deqing Sun, Ming-Hsuan Yang, Jan Kautz

Despite the long history of image and video stitching research, existing academic and commercial solutions still produce strong artifacts.

Autonomous Driving Spatial Interpolation

Unsupervised Video Interpolation Using Cycle Consistency

1 code implementation ICCV 2019 Fitsum A. Reda, Deqing Sun, Aysegul Dundar, Mohammad Shoeybi, Guilin Liu, Kevin J. Shih, Andrew Tao, Jan Kautz, Bryan Catanzaro

We further introduce a pseudo supervised loss term that enforces the interpolated frames to be consistent with predictions of a pre-trained interpolation model.

 Ranked #1 on Video Frame Interpolation on UCF101 (PSNR (sRGB) metric)

Video Frame Interpolation

Pixel-Adaptive Convolutional Neural Networks

2 code implementations CVPR 2019 Hang Su, Varun Jampani, Deqing Sun, Orazio Gallo, Erik Learned-Miller, Jan Kautz

In addition, we also demonstrate that PAC can be used as a drop-in replacement for convolution layers in pre-trained networks, resulting in consistent performance improvements.

A Fusion Approach for Multi-Frame Optical Flow Estimation

2 code implementations23 Oct 2018 Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz

To date, top-performing optical flow estimation methods only take pairs of consecutive frames into account.

Optical Flow Estimation

Models Matter, So Does Training: An Empirical Study of CNNs for Optical Flow Estimation

2 code implementations14 Sep 2018 Deqing Sun, Xiaodong Yang, Ming-Yu Liu, Jan Kautz

We investigate two crucial and closely related aspects of CNNs for optical flow estimation: models and training.

Optical Flow Estimation

Rendering Portraitures from Monocular Camera and Beyond

no code implementations ECCV 2018 Xiangyu Xu, Deqing Sun, Sifei Liu, Wenqi Ren, Yu-Jin Zhang, Ming-Hsuan Yang, Jian Sun

Specifically, we first exploit Convolutional Neural Networks to estimate the relative depth and portrait segmentation maps from a single input image.

Image Matting Portrait Segmentation

Learning Data Terms for Non-blind Deblurring

no code implementations ECCV 2018 Jiangxin Dong, Jinshan Pan, Deqing Sun, Zhixun Su, Ming-Hsuan Yang

We propose a simple and effective discriminative framework to learn data terms that can adaptively handle blurred images in the presence of severe noise and outliers.


Superpixel Sampling Networks

2 code implementations ECCV 2018 Varun Jampani, Deqing Sun, Ming-Yu Liu, Ming-Hsuan Yang, Jan Kautz

Superpixels provide an efficient low/mid-level representation of image data, which greatly reduces the number of image primitives for subsequent vision tasks.


Learning Superpixels With Segmentation-Aware Affinity Loss

no code implementations CVPR 2018 Wei-Chih Tu, Ming-Yu Liu, Varun Jampani, Deqing Sun, Shao-Yi Chien, Ming-Hsuan Yang, Jan Kautz

Specifically, we propose a new loss function that takes the segmentation error into account for affinity learning.


Competitive Collaboration: Joint Unsupervised Learning of Depth, Camera Motion, Optical Flow and Motion Segmentation

1 code implementation CVPR 2019 Anurag Ranjan, Varun Jampani, Lukas Balles, Kihwan Kim, Deqing Sun, Jonas Wulff, Michael J. Black

We address the unsupervised learning of several interconnected problems in low-level vision: single view depth prediction, camera motion estimation, optical flow, and segmentation of a video into the static scene and moving regions.

Depth Prediction Monocular Depth Estimation +3

SPLATNet: Sparse Lattice Networks for Point Cloud Processing

2 code implementations CVPR 2018 Hang Su, Varun Jampani, Deqing Sun, Subhransu Maji, Evangelos Kalogerakis, Ming-Hsuan Yang, Jan Kautz

We present a network architecture for processing point clouds that directly operates on a collection of points represented as a sparse set of samples in a high-dimensional lattice.

Ranked #25 on Semantic Segmentation on ScanNet (test mIoU metric)

3D Part Segmentation 3D Semantic Segmentation

Learning Binary Residual Representations for Domain-specific Video Streaming

no code implementations14 Dec 2017 Yi-Hsuan Tsai, Ming-Yu Liu, Deqing Sun, Ming-Hsuan Yang, Jan Kautz

Specifically, we target a streaming setting where the videos to be streamed from a server to a client are all in the same domain and they have to be compressed to a small size for low-latency transmission.

Video Compression

Cascaded Scene Flow Prediction using Semantic Segmentation

no code implementations26 Jul 2017 Zhile Ren, Deqing Sun, Jan Kautz, Erik B. Sudderth

Given two consecutive frames from a pair of stereo cameras, 3D scene flow methods simultaneously estimate the 3D geometry and motion of the observed scene.

Autonomous Driving General Classification +3

Blind Image Deblurring Using Dark Channel Prior

no code implementations CVPR 2016 Jinshan Pan, Deqing Sun, Hanspeter Pfister, Ming-Hsuan Yang

Therefore, enforcing the sparsity of the dark channel helps blind deblurring on various scenarios, including natural, face, text, and low-illumination images.

Blind Image Deblurring Image Deblurring

Layered RGBD Scene Flow Estimation

no code implementations CVPR 2015 Deqing Sun, Erik B. Sudderth, Hanspeter Pfister

As consumer depth sensors become widely available, estimating scene flow from RGBD sequences has received increasing attention.

Optical Flow Estimation Scene Flow Estimation +1

Local Layering for Joint Motion Estimation and Occlusion Detection

no code implementations CVPR 2014 Deqing Sun, Ce Liu, Hanspeter Pfister

To handle such situations, we propose a local layering model where motion and occlusion relationships are inferred jointly.

Motion Estimation Optical Flow Estimation

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