230 citations · 1.1k across the 84 of their papers we have counts for
13 papers · 1 filter
Superpixel Soup: Monocular Dense 3D Reconstruction of a Complex Dynamic Scene
Suryansh Kumar, Yuchao Dai, Hongdong Li
This work addresses the task of dense 3D reconstruction of a complex dynamic scene from images. The prevailing idea to solve this task is composed of a sequence of steps and is dep…
Joint Stereo Video Deblurring, Scene Flow Estimation and Moving Object Segmentation
Liyuan Pan, Yuchao Dai, Miaomiao Liu +2
Stereo videos for the dynamic scenes often show unpleasant blurred effects due to the camera motion and the multiple moving objects with large depth variations. Given consecutive b…
MVS^2: Deep Unsupervised Multi-view Stereo with Multi-View Symmetry
Yuchao Dai, Zhidong Zhu, Zhibo Rao +1
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. Such…
IoU Loss for 2D/3D Object Detection
Dingfu Zhou, Jin Fang, Xibin Song +4
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 sta…
MSDC-Net: Multi-Scale Dense and Contextual Networks for Automated Disparity Map for Stereo Matching
Zhibo Rao, Mingyi He, Yuchao Dai +3
Disparity prediction from stereo images is essential to computer vision applications including autonomous driving, 3D model reconstruction, and object detection. To predict accurat…
Noise-Aware Unsupervised Deep Lidar-Stereo Fusion
Xuelian Cheng, Yiran Zhong, Yuchao Dai +2
In this paper, we present LidarStereoNet, the first unsupervised Lidar-stereo fusion network, which can be trained in an end-to-end manner without the need of ground truth depth ma…
Deep Stacked Hierarchical Multi-patch Network for Image Deblurring
Hongguang Zhang, Yuchao Dai, Hongdong Li +1
Despite deep end-to-end learning methods have shown their superiority in removing non-uniform motion blur, there still exist major challenges with the current multi-scale and scale…
Multi-scale Cross-form Pyramid Network for Stereo Matching
Zhidong Zhu, Mingyi He, Yuchao Dai +2
Stereo matching plays an indispensable part in autonomous driving, robotics and 3D scene reconstruction. We propose a novel deep learning architecture, which called CFP-Net, a Cros…
Unsupervised Deep Epipolar Flow for Stationary or Dynamic Scenes
Yiran Zhong, Pan Ji, Jianyuan Wang +2
Unsupervised deep learning for optical flow computation has achieved promising results. Most existing deep-net based methods rely on image brightness consistency and local smoothne…
Dense Depth Estimation of a Complex Dynamic Scene without Explicit 3D Motion Estimation
Suryansh Kumar, Ram Srivatsav Ghorakavi, Yuchao Dai +1
Recent geometric methods need reliable estimates of 3D motion parameters to procure accurate dense depth map of a complex dynamic scene from monocular images \cite{kumar2017monocul…
Ground Plane based Absolute Scale Estimation for Monocular Visual Odometry
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. By using different kinds of cues, var…
High Frame Rate Video Reconstruction based on an Event Camera
Liyuan Pan, Richard Hartley, Cedric Scheerlinck +3
Event-based cameras measure intensity changes (called `events') with microsecond accuracy under high-speed motion and challenging lighting conditions. With the `active pixel sensor…
Single Image Deblurring and Camera Motion Estimation with Depth Map
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 main…