Search Results for author: Yuchao Dai

Found 87 papers, 23 papers with code

Efficient Spatial-Temporal Information Fusion for LiDAR-Based 3D Moving Object Segmentation

1 code implementation5 Jul 2022 Jiadai Sun, Yuchao Dai, Xianjing Zhang, Jintao Xu, Rui Ai, Weihao Gu, Xieyuanli Chen

We also use a point refinement module via 3D sparse convolution to fuse the information from both LiDAR range image and point cloud representations and reduce the artifacts on the borders of the objects.

Autonomous Driving Semantic Segmentation

Neural Deformable Voxel Grid for Fast Optimization of Dynamic View Synthesis

no code implementations15 Jun 2022 Xiang Guo, GuanYing Chen, Yuchao Dai, Xiaoqing Ye, Jiadai Sun, Xiao Tan, Errui Ding

However, NeRF and its variants generally require a lengthy per-scene training procedure, where a multi-layer perceptron (MLP) is fitted to the captured images.

Novel View Synthesis

Context-Aware Video Reconstruction for Rolling Shutter Cameras

1 code implementation CVPR 2022 Bin Fan, Yuchao Dai, Zhiyuan Zhang, Qi Liu, Mingyi He

Then, a refinement scheme is proposed to guide the GS frame synthesis along with bilateral occlusion masks to produce high-fidelity GS video frames at arbitrary times.

Motion Compensation Video Reconstruction

Towards Deeper Understanding of Camouflaged Object Detection

1 code implementation23 May 2022 Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Nick Barnes, Deng-Ping Fan

To detect and segment the whole scope of a camouflaged object, camouflaged object detection (COD) is introduced as a binary segmentation task, with the binary ground truth camouflage map indicating the exact regions of the camouflaged objects.

object-detection Object Detection

Deep Non-rigid Structure-from-Motion: A Sequence-to-Sequence Translation Perspective

no code implementations10 Apr 2022 Hui Deng, Tong Zhang, Yuchao Dai, Jiawei Shi, Yiran Zhong, Hongdong Li

In this paper, we propose to model deep NRSfM from a sequence-to-sequence translation perspective, where the input 2D frame sequence is taken as a whole to reconstruct the deforming 3D non-rigid shape sequence.

3D Reconstruction Translation

VRNet: Learning the Rectified Virtual Corresponding Points for 3D Point Cloud Registration

no code implementations24 Mar 2022 Zhiyuan Zhang, Jiadai Sun, Yuchao Dai, Bin Fan, Mingyi He

3D point cloud registration is fragile to outliers, which are labeled as the points without corresponding points.

Point Cloud Registration

A Representation Separation Perspective to Correspondences-free Unsupervised 3D Point Cloud Registration

no code implementations24 Mar 2022 Zhiyuan Zhang, Jiadai Sun, Yuchao Dai, Dingfu Zhou, Xibin Song, Mingyi He

Existing correspondences-free methods generally learn the holistic representation of the entire point cloud, which is fragile for partial and noisy point clouds.

Point Cloud Registration

Efficient Multi-View Stereo by Iterative Dynamic Cost Volume

no code implementations CVPR 2022 Shaoqian Wang, Bo Li, Yuchao Dai

Specifically, a lightweight 3D CNN is utilized to generate the coarsest initial depth map which is essential to launch the GRU and guarantee a fast convergence.

MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation

no code implementations29 Nov 2021 Jiadai Sun, Yuxin Mao, Yuchao Dai, Yiran Zhong, Jianyuan Wang

The task of semi-supervised video object segmentation (VOS) has been greatly advanced and state-of-the-art performance has been made by dense matching-based methods.

Semantic Segmentation Semi-Supervised Video Object Segmentation +1

A General Divergence Modeling Strategy for Salient Object Detection

no code implementations23 Nov 2021 Xinyu Tian, Jing Zhang, Yuchao Dai

Given multiple saliency annotations, we introduce a general divergence modeling strategy via random sampling, and apply our strategy to an ensemble based framework and three latent variable model based solutions.

object-detection Object Detection +1

Dense Uncertainty Estimation via an Ensemble-based Conditional Latent Variable Model

no code implementations22 Nov 2021 Jing Zhang, Yuchao Dai, Mehrtash Harandi, Yiran Zhong, Nick Barnes, Richard Hartley

Uncertainty estimation has been extensively studied in recent literature, which can usually be classified as aleatoric uncertainty and epistemic uncertainty.

object-detection Object Detection

End-to-end Learning the Partial Permutation Matrix for Robust 3D Point Cloud Registration

no code implementations28 Oct 2021 Zhiyuan Zhang, Jiadai Sun, Yuchao Dai, Dingfu Zhou, Xibin Song, Mingyi He

Even though considerable progress has been made in deep learning-based 3D point cloud processing, how to obtain accurate correspondences for robust registration remains a major challenge because existing hard assignment methods cannot deal with outliers naturally.

Point Cloud Registration

Dense Uncertainty Estimation

1 code implementation13 Oct 2021 Jing Zhang, Yuchao Dai, Mochu Xiang, Deng-Ping Fan, Peyman Moghadam, Mingyi He, Christian Walder, Kaihao Zhang, Mehrtash Harandi, Nick Barnes

Deep neural networks can be roughly divided into deterministic neural networks and stochastic neural networks. The former is usually trained to achieve a mapping from input space to output space via maximum likelihood estimation for the weights, which leads to deterministic predictions during testing.

Decision Making

RGB-D Saliency Detection via Cascaded Mutual Information Minimization

1 code implementation ICCV 2021 Jing Zhang, Deng-Ping Fan, Yuchao Dai, Xin Yu, Yiran Zhong, Nick Barnes, Ling Shao

In this paper, we introduce a novel multi-stage cascaded learning framework via mutual information minimization to "explicitly" model the multi-modal information between RGB image and depth data.

Saliency Detection

PR-RRN: Pairwise-Regularized Residual-Recursive Networks for Non-rigid Structure-from-Motion

no code implementations ICCV 2021 Haitian Zeng, Yuchao Dai, Xin Yu, Xiaohan Wang, Yi Yang

As NRSfM is a highly under-constrained problem, we propose two new pairwise regularization to further regularize the reconstruction.

SUNet: Symmetric Undistortion Network for Rolling Shutter Correction

no code implementations ICCV 2021 Bin Fan, Yuchao Dai, Mingyi He

The vast majority of modern consumer-grade cameras employ a rolling shutter mechanism, leading to image distortions if the camera moves during image acquisition.

Complementary Patch for Weakly Supervised Semantic Segmentation

1 code implementation ICCV 2021 Fei Zhang, Chaochen Gu, Chenyue Zhang, Yuchao Dai

Therefore, a CAM with more information related to object seeds can be obtained by narrowing down the gap between the sum of CAMs generated by the CP Pair and the original CAM.

Weakly-Supervised Semantic Segmentation

Exploring Depth Contribution for Camouflaged Object Detection

no code implementations24 Jun 2021 Mochu Xiang, Jing Zhang, Yunqiu Lv, Aixuan Li, Yiran Zhong, Yuchao Dai

In this paper, we study the depth contribution for camouflaged object detection, where the depth maps are generated with existing monocular depth estimation (MDE) methods.

Monocular Depth Estimation object-detection +3

Generative Transformer for Accurate and Reliable Salient Object Detection

1 code implementation20 Apr 2021 Yuxin Mao, Jing Zhang, Zhexiong Wan, Yuchao Dai, Aixuan Li, Yunqiu Lv, Xinyu Tian, Deng-Ping Fan, Nick Barnes

We apply the proposed inferential generative adversarial network (iGAN) to both fully and weakly supervised salient object detection, and explain that iGAN within the transformer framework leads to both accurate and reliable salient object detection.

Camouflaged Object Segmentation Machine Translation +5

CFNet: Cascade and Fused Cost Volume for Robust Stereo Matching

2 code implementations CVPR 2021 Zhelun Shen, Yuchao Dai, Zhibo Rao

In this paper, we propose CFNet, a Cascade and Fused cost volume based network to improve the robustness of the stereo matching network.

Disparity Estimation Stereo Matching

Uncertainty-aware Joint Salient Object and Camouflaged Object Detection

1 code implementation CVPR 2021 Aixuan Li, Jing Zhang, Yunqiu Lv, Bowen Liu, Tong Zhang, Yuchao Dai

Visual salient object detection (SOD) aims at finding the salient object(s) that attract human attention, while camouflaged object detection (COD) on the contrary intends to discover the camouflaged object(s) that hidden in the surrounding.

object-detection Object Detection +1

Simultaneously Localize, Segment and Rank the Camouflaged Objects

1 code implementation CVPR 2021 Yunqiu Lv, Jing Zhang, Yuchao Dai, Aixuan Li, Bowen Liu, Nick Barnes, Deng-Ping Fan

With the above understanding about camouflaged objects, we present the first ranking based COD network (Rank-Net) to simultaneously localize, segment and rank camouflaged objects.

object-detection Object Detection

Neural Image Compression via Attentional Multi-Scale Back Projection and Frequency Decomposition

no code implementations ICCV 2021 Ge Gao, Pei You, Rong pan, Shunyuan Han, Yuanyuan Zhang, Yuchao Dai, Hojae Lee

In recent years, neural image compression emerges as a rapidly developing topic in computer vision, where the state-of-the-art approaches now exhibit superior compression performance than their conventional counterparts.

Image Compression MS-SSIM +1

Inverting a Rolling Shutter Camera: Bring Rolling Shutter Images to High Framerate Global Shutter Video

no code implementations ICCV 2021 Bin Fan, Yuchao Dai

In this paper, we propose to invert the above RS imaging mechanism, i. e., recovering a high framerate GS video from consecutive RS images to achieve RS temporal super-resolution (RSSR).

Optical Flow Estimation Super-Resolution

UASNet: Uncertainty Adaptive Sampling Network for Deep Stereo Matching

no code implementations ICCV 2021 Yamin Mao, Zhihua Liu, Weiming Li, Yuchao Dai, Qiang Wang, Yun-Tae Kim, Hong-Seok Lee

Extensive experiments show that the proposed method achieves the highest ground truth covering ratio compared with other cascade cost volume based stereo matching methods.

Stereo Matching

Class Attention Network for Semantic Segmentation of Remote Sensing Images

no code implementations31 Dec 2020 Zhibo Rao, Mingyi He, Yuchao Dai

In this paper, we proposed a novel class attention module and decomposition-fusion strategy to cope with imbalanced labels.

Scene Parsing Semantic Segmentation

Uncertainty-Aware Deep Calibrated Salient Object Detection

no code implementations10 Dec 2020 Jing Zhang, Yuchao Dai, Xin Yu, Mehrtash Harandi, Nick Barnes, Richard Hartley

Existing deep neural network based salient object detection (SOD) methods mainly focus on pursuing high network accuracy.

object-detection Object Detection +1

Depth Completion using Piecewise Planar Model

no code implementations6 Dec 2020 Yiran Zhong, Yuchao Dai, Hongdong Li

More specifically, we represent the desired depth map as a collection of 3D planar and the reconstruction problem is formulated as the optimization of planar parameters.

Depth Completion Visual Odometry

Efficient Depth Completion Using Learned Bases

no code implementations2 Dec 2020 Yiran Zhong, Yuchao Dai, Hongdong Li

The given sparse depth points are served as a data term to constrain the weighting process.

Depth Completion

Displacement-Invariant Matching Cost Learning for Accurate Optical Flow Estimation

2 code implementations NeurIPS 2020 Jianyuan Wang, Yiran Zhong, Yuchao Dai, Kaihao Zhang, Pan Ji, Hongdong Li

Learning matching costs has been shown to be critical to the success of the state-of-the-art deep stereo matching methods, in which 3D convolutions are applied on a 4D feature volume to learn a 3D cost volume.

Optical Flow Estimation Stereo Matching

Hierarchical Neural Architecture Search for Deep Stereo Matching

1 code implementation NeurIPS 2020 Xuelian Cheng, Yiran Zhong, Mehrtash Harandi, Yuchao Dai, Xiaojun Chang, Tom Drummond, Hongdong Li, ZongYuan Ge

To reduce the human efforts in neural network design, Neural Architecture Search (NAS) has been applied with remarkable success to various high-level vision tasks such as classification and semantic segmentation.

Neural Architecture Search Semantic Segmentation +2

PRAFlow_RVC: Pyramid Recurrent All-Pairs Field Transforms for Optical Flow Estimation in Robust Vision Challenge 2020

no code implementations14 Sep 2020 Zhexiong Wan, Yuxin Mao, Yuchao Dai

Optical flow estimation is an important computer vision task, which aims at estimating the dense correspondences between two frames.

Optical Flow Estimation

Uncertainty Inspired RGB-D Saliency Detection

4 code implementations7 Sep 2020 Jing Zhang, Deng-Ping Fan, Yuchao Dai, Saeed Anwar, Fatemeh Saleh, Sadegh Aliakbarian, Nick Barnes

Our framework includes two main models: 1) a generator model, which maps the input image and latent variable to stochastic saliency prediction, and 2) an inference model, which gradually updates the latent variable by sampling it from the true or approximate posterior distribution.

RGB-D Salient Object Detection RGB Salient Object Detection +1

MSMD-Net: Deep Stereo Matching with Multi-scale and Multi-dimension Cost Volume

no code implementations23 Jun 2020 Zhelun Shen, Yuchao Dai, Zhibo Rao

At the multi-dimension level, we additionally construct a 3D warped correlation volume and use it to refine the initial disparity map with residual learning.

Disparity Estimation Stereo Matching

Dense Non-Rigid Structure from Motion: A Manifold Viewpoint

no code implementations15 Jun 2020 Suryansh Kumar, Luc van Gool, Carlos E. P. de Oliveira, Anoop Cherian, Yuchao Dai, Hongdong Li

Assuming that a deforming shape is composed of a union of local linear subspace and, span a global low-rank space over multiple frames enables us to efficiently model complex non-rigid deformations.

Relative Pose Estimation for Stereo Rolling Shutter Cameras

no code implementations14 Jun 2020 Ke Wang, Bin Fan, Yuchao Dai

In this paper, we present a novel linear algorithm to estimate the 6 DoF relative pose from consecutive frames of stereo rolling shutter (RS) cameras.

Pose Estimation

Channel Attention based Iterative Residual Learning for Depth Map Super-Resolution

no code implementations CVPR 2020 Xibin Song, Yuchao Dai, Dingfu Zhou, Liu Liu, Wei Li, Hongdng Li, Ruigang Yang

Second, we propose a new framework for real-world DSR, which consists of four modules : 1) An iterative residual learning module with deep supervision to learn effective high-frequency components of depth maps in a coarse-to-fine manner; 2) A channel attention strategy to enhance channels with abundant high-frequency components; 3) A multi-stage fusion module to effectively re-exploit the results in the coarse-to-fine process; and 4) A depth refinement module to improve the depth map by TGV regularization and input loss.

Depth Map Super-Resolution

Superpixel Soup: Monocular Dense 3D Reconstruction of a Complex Dynamic Scene

no code implementations19 Nov 2019 Suryansh Kumar, Yuchao Dai, Hongdong Li

We assume that a dynamic scene can be approximated by numerous piecewise planar surfaces, where each planar surface enjoys its own rigid motion, and the global change in the scene between two frames is as-rigid-as-possible (ARAP).

3D Reconstruction

Joint Stereo Video Deblurring, Scene Flow Estimation and Moving Object Segmentation

no code implementations6 Oct 2019 Liyuan Pan, Yuchao Dai, Miaomiao Liu, Fatih Porikli, Quan Pan

Under our model, these three tasks are naturally connected and expressed as the parameter estimation of 3D scene structure and camera motion (structure and motion for the dynamic scenes).

Deblurring Scene Flow Estimation +1

MVS^2: Deep Unsupervised Multi-view Stereo with Multi-View Symmetry

no code implementations30 Aug 2019 Yuchao Dai, Zhidong Zhu, Zhibo Rao, Bo Li

The success of existing deep-learning based multi-view stereo (MVS) approaches greatly depends on the availability of large-scale supervision in the form of dense depth maps.

IoU Loss for 2D/3D Object Detection

1 code implementation11 Aug 2019 Dingfu Zhou, Jin Fang, Xibin Song, Chenye Guan, Junbo Yin, Yuchao Dai, Ruigang Yang

In 2D/3D object detection task, Intersection-over-Union (IoU) has been widely employed as an evaluation metric to evaluate the performance of different detectors in the testing stage.

2D object detection 3D Object Detection +1

MSDC-Net: Multi-Scale Dense and Contextual Networks for Automated Disparity Map for Stereo Matching

no code implementations25 Apr 2019 Zhibo Rao, Mingyi He, Yuchao Dai, Zhidong Zhu, Bo Li, Renjie He

The multi-scale residual 3D convolution module learns the different scale geometry context from the cost volume which aggregated by the multi-scale fusion 2D convolution module.

Autonomous Driving object-detection +3

Multi-scale Cross-form Pyramid Network for Stereo Matching

no code implementations25 Apr 2019 Zhidong Zhu, Mingyi He, Yuchao Dai, Zhibo Rao, Bo Li

The network consists of three modules: Multi-Scale 2D local feature extraction module, Cross-form spatial pyramid module and Multi-Scale 3D Feature Matching and Fusion module.

3D Feature Matching 3D Scene Reconstruction +3

Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes

no code implementations CVPR 2019 Yiran Zhong, Pan Ji, Jianyuan Wang, Yuchao Dai, Hongdong Li

In this paper, we propose Deep Epipolar Flow, an unsupervised optical flow method which incorporates global geometric constraints into network learning.

Optical Flow Estimation

High Frame Rate Video Reconstruction based on an Event Camera

1 code implementation12 Mar 2019 Liyuan Pan, Richard Hartley, Cedric Scheerlinck, Miaomiao Liu, Xin Yu, Yuchao Dai

Based on the abundant event data alongside a low frame rate, easily blurred images, we propose a simple yet effective approach to reconstruct high-quality and high frame rate sharp videos.

Video Generation Video Reconstruction

Ground Plane based Absolute Scale Estimation for Monocular Visual Odometry

no code implementations3 Mar 2019 Dingfu Zhou, Yuchao Dai, Hongdong Li

Recovering the absolute metric scale from a monocular camera is a challenging but highly desirable problem for monocular camera-based systems.

Monocular Visual Odometry

Single Image Deblurring and Camera Motion Estimation with Depth Map

no code implementations1 Mar 2019 Liyuan Pan, Yuchao Dai, Miaomiao Liu

Camera shake during exposure is a major problem in hand-held photography, as it causes image blur that destroys details in the captured images.~In the real world, such blur is mainly caused by both the camera motion and the complex scene structure.~While considerable existing approaches have been proposed based on various assumptions regarding the scene structure or the camera motion, few existing methods could handle the real 6 DoF camera motion.~In this paper, we propose to jointly estimate the 6 DoF camera motion and remove the non-uniform blur caused by camera motion by exploiting their underlying geometric relationships, with a single blurry image and its depth map (either direct depth measurements, or a learned depth map) as input.~We formulate our joint deblurring and 6 DoF camera motion estimation as an energy minimization problem which is solved in an alternative manner.

Deblurring Image Deblurring +1

Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation

no code implementations11 Feb 2019 Suryansh Kumar, Ram Srivatsav Ghorakavi, Yuchao Dai, Hongdong Li

Given per-pixel optical flow correspondences between two consecutive frames and, the sparse depth prior for the reference frame, we show that, we can effectively recover the dense depth map for the successive frames without solving for 3D motion parameters.

Depth Estimation Motion Estimation +1

ApolloCar3D: A Large 3D Car Instance Understanding Benchmark for Autonomous Driving

no code implementations CVPR 2019 Xibin Song, Peng Wang, Dingfu Zhou, Rui Zhu, Chenye Guan, Yuchao Dai, Hao Su, Hongdong Li, Ruigang Yang

Specifically, we first segment each car with a pre-trained Mask R-CNN, and then regress towards its 3D pose and shape based on a deformable 3D car model with or without using semantic keypoints.

3D Car Instance Understanding Autonomous Driving

Bringing a Blurry Frame Alive at High Frame-Rate with an Event Camera

1 code implementation CVPR 2019 Liyuan Pan, Cedric Scheerlinck, Xin Yu, Richard Hartley, Miaomiao Liu, Yuchao Dai

In this paper, we propose a simple and effective approach, the \textbf{Event-based Double Integral (EDI)} model, to reconstruct a high frame-rate, sharp video from a single blurry frame and its event data.

Video Generation

Deeply Supervised Depth Map Super-Resolution as Novel View Synthesis

no code implementations27 Aug 2018 Xibin Song, Yuchao Dai, Xueying Qin

However, there still exist two major issues with these DCNN based depth map super-resolution methods that hinder the performance: i) The low-resolution depth maps either need to be up-sampled before feeding into the network or substantial deconvolution has to be used; and ii) The supervision (high-resolution depth maps) is only applied at the end of the network, thus it is difficult to handle large up-sampling factors, such as $\times 8, \times 16$.

Depth Map Super-Resolution Novel View Synthesis

Stochastic Attraction-Repulsion Embedding for Large Scale Image Localization

5 code implementations ICCV 2019 Liu Liu, Hongdong Li, Yuchao Dai

This paper tackles the problem of large-scale image-based localization (IBL) where the spatial location of a query image is determined by finding out the most similar reference images in a large database.

Image-Based Localization Representation Learning

Stereo Computation for a Single Mixture Image

no code implementations ECCV 2018 Yiran Zhong, Yuchao Dai, Hongdong Li

This paper proposes an original problem of \emph{stereo computation from a single mixture image}-- a challenging problem that had not been researched before.

Stereo Matching Stereo Matching Hand

3D Geometry-Aware Semantic Labeling of Outdoor Street Scenes

no code implementations13 Aug 2018 Yiran Zhong, Yuchao Dai, Hongdong Li

This paper is concerned with the problem of how to better exploit 3D geometric information for dense semantic image labeling.

Open-World Stereo Video Matching with Deep RNN

no code implementations ECCV 2018 Yiran Zhong, Hongdong Li, Yuchao Dai

Deep Learning based stereo matching methods have shown great successes and achieved top scores across different benchmarks.

Stereo Matching Stereo Matching Hand

Occluded Joints Recovery in 3D Human Pose Estimation based on Distance Matrix

no code implementations30 Jul 2018 Xiang Guo, Yuchao Dai

In this paper, we propose to address the problem of single image 3D human pose estimation with occluded measurements by exploiting the Euclidean distance matrix (EDM).

3D Human Pose Estimation

Scalable Dense Non-rigid Structure-from-Motion: A Grassmannian Perspective

no code implementations CVPR 2018 Suryansh Kumar, Anoop Cherian, Yuchao Dai, Hongdong Li

To address these issues, in this paper, we propose a new approach for dense NRSfM by modeling the problem on a Grassmann manifold.

Depth Map Completion by Jointly Exploiting Blurry Color Images and Sparse Depth Maps

no code implementations27 Nov 2017 Liyuan Pan, Yuchao Dai, Miaomiao Liu, Fatih Porikli

In this paper, we propose to tackle the problem of depth map completion by jointly exploiting the blurry color image sequences and the sparse depth map measurements, and present an energy minimization based formulation to simultaneously complete the depth maps, estimate the scene flow and deblur the color images.

Efficient Global 2D-3D Matching for Camera Localization in a Large-Scale 3D Map

no code implementations ICCV 2017 Liu Liu, Hongdong Li, Yuchao Dai

In this paper, we introduce a global method which harnesses global contextual information exhibited both within the query image and among all the 3D points in the map.

3D Feature Matching Camera Localization

Self-Supervised Learning for Stereo Matching with Self-Improving Ability

no code implementations4 Sep 2017 Yiran Zhong, Yuchao Dai, Hongdong Li

Exiting deep-learning based dense stereo matching methods often rely on ground-truth disparity maps as the training signals, which are however not always available in many situations.

Self-Supervised Learning Stereo Matching +1

Deep Edge-Aware Saliency Detection

no code implementations15 Aug 2017 Jing Zhang, Yuchao Dai, Fatih Porikli, Mingyi He

There has been profound progress in visual saliency thanks to the deep learning architectures, however, there still exist three major challenges that hinder the detection performance for scenes with complex compositions, multiple salient objects, and salient objects of diverse scales.

Saliency Detection

Monocular Depth Estimation with Hierarchical Fusion of Dilated CNNs and Soft-Weighted-Sum Inference

1 code implementation2 Aug 2017 Bo Li, Yuchao Dai, Mingyi He

Extensive experiments on the NYU Depth V2 and KITTI datasets show the superiority of our method compared with current state-of-the-art methods.

Monocular Depth Estimation Quantization +1

Pixel-variant Local Homography for Fisheye Stereo Rectification Minimizing Resampling Distortion

no code implementations12 Jul 2017 Dingfu Zhou, Yuchao Dai, Hongdong Li

First, we prove that there indeed exist enough degrees of freedom to apply pixel-wise local homography for stereo rectification.

3D Reconstruction Stereo Matching +1

Dense Non-rigid Structure-from-Motion Made Easy - A Spatial-Temporal Smoothness based Solution

no code implementations27 Jun 2017 Yuchao Dai, Huizhong Deng, Mingyi He

Second, we propose to exploit the spatial smoothness by resorting to the Laplacian of the 3D non-rigid shape.

Integrated Deep and Shallow Networks for Salient Object Detection

no code implementations2 Jun 2017 Jing Zhang, Bo Li, Yuchao Dai, Fatih Porikli, Mingyi He

Then the results from deep FCNN and RBD are concatenated to feed into a shallow network to map the concatenated feature maps to saliency maps.

object-detection RGB Salient Object Detection +2

Spatial-Temporal Union of Subspaces for Multi-body Non-rigid Structure-from-Motion

no code implementations14 May 2017 Suryansh Kumar, Yuchao Dai, Hongdong Li

This spatio-temporal representation not only provides competitive 3D reconstruction but also outputs robust segmentation of multiple non-rigid objects.

3D Reconstruction

Single image depth estimation by dilated deep residual convolutional neural network and soft-weight-sum inference

1 code implementation27 Apr 2017 Bo Li, Yuchao Dai, Huahui Chen, Mingyi He

This paper proposes a new residual convolutional neural network (CNN) architecture for single image depth estimation.

Depth Estimation

Skeleton based action recognition using translation-scale invariant image mapping and multi-scale deep cnn

no code implementations19 Apr 2017 Bo Li, Mingyi He, Xuelian Cheng, Yu-cheng Chen, Yuchao Dai

Especially on the largest and challenge NTU RGB+D, UTD-MHAD, and MSRC-12 dataset, our method outperforms other methods by a large margion, which proves the efficacy of the proposed method.

Action Recognition Image Classification +2

Skeleton Boxes: Solving skeleton based action detection with a single deep convolutional neural network

no code implementations19 Apr 2017 Bo Li, Huahui Chen, Yu-cheng Chen, Yuchao Dai, Mingyi He

However, due to the difficulty in representing the 3D skeleton video and the lack of training data, action detection from streaming 3D skeleton video still lags far behind its recognition counterpart and image based object detection.

Action Detection Action Recognition +2

Simultaneous Stereo Video Deblurring and Scene Flow Estimation

no code implementations CVPR 2017 Liyuan Pan, Yuchao Dai, Miaomiao Liu, Fatih Porikli

Unlike the existing approach [31] which used a pre-computed scene flow, we propose a single framework to jointly estimate the scene flow and deblur the image, where the motion cues from scene flow estimation and blur information could reinforce each other, and produce superior results than the conventional scene flow estimation or stereo deblurring methods.

Deblurring Scene Flow Estimation

Multi-body Non-rigid Structure-from-Motion

no code implementations15 Jul 2016 Suryansh Kumar, Yuchao Dai, Hongdong Li

Recent progress have extended SFM to the areas of {multi-body SFM} (where there are {multiple rigid} relative motions in the scene), as well as {non-rigid SFM} (where there is a single non-rigid, deformable object or scene).

3D Reconstruction

Deep Depth Super-Resolution : Learning Depth Super-Resolution using Deep Convolutional Neural Network

no code implementations7 Jul 2016 Xibin Song, Yuchao Dai, Xueying Qin

In this paper, we bridge up the gap and extend the success of deep convolutional neural network to depth super-resolution.

Image Super-Resolution

Robust and Efficient Relative Pose with a Multi-camera System for Autonomous Vehicle in Highly Dynamic Environments

no code implementations12 May 2016 Liu Liu, Hongdong Li, Yuchao Dai

When the solver is used in combination with RANSAC, we are able to quickly prune unpromising hypotheses, significantly improve the chance of finding inliers.

Motion Estimation

Robust Optical Flow Estimation of Double-Layer Images under Transparency or Reflection

no code implementations CVPR 2016 Jiaolong Yang, Hongdong Li, Yuchao Dai, Robby T. Tan

This paper deals with a challenging, frequently encountered, yet not properly investigated problem in two-frame optical flow estimation.

Optical Flow Estimation

Rolling Shutter Camera Relative Pose: Generalized Epipolar Geometry

no code implementations CVPR 2016 Yuchao Dai, Hongdong Li, Laurent Kneip

The vast majority of modern consumer-grade cameras employ a rolling shutter mechanism.

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