415 citations · 715 across the 25 of their papers we have counts for
26 papers
CrossZoom: Simultaneously Motion Deblurring and Event Super-Resolving
Chi Zhang, Xiang Zhang, Mingyuan Lin +5
Even though the collaboration between traditional and neuromorphic event cameras brings prosperity to frame-event based vision applications, the performance is still confined by th…
Generalizing Event-Based Motion Deblurring in Real-World Scenarios
Xiang Zhang, Lei Yu, Wen Yang +2
Event-based motion deblurring has shown promising results by exploiting low-latency events. However, current approaches are limited in their practical usage, as they assume the sam…
Video Frame Interpolation with Stereo Event and Intensity Camera
Chao Ding, Mingyuan Lin, Haijian Zhang +2
The stereo event-intensity camera setup is widely applied to leverage the advantages of both event cameras with low latency and intensity cameras that capture accurate brightness a…
Self-Supervised Scene Dynamic Recovery from Rolling Shutter Images and Events
Yangguang Wang, Xiang Zhang, Mingyuan Lin +4
Scene Dynamic Recovery (SDR) by inverting distorted Rolling Shutter (RS) images to an undistorted high frame-rate Global Shutter (GS) video is a severely ill-posed problem due to t…
Dynamic Coarse-to-Fine Learning for Oriented Tiny Object Detection
Chang Xu, Jian Ding, Jinwang Wang +4
Detecting arbitrarily oriented tiny objects poses intense challenges to existing detectors, especially for label assignment. Despite the exploration of adaptive label assignment in…
DIPNet: Efficiency Distillation and Iterative Pruning for Image Super-Resolution
Lei Yu, Xinpeng Li, Youwei Li +4
Efficient deep learning-based approaches have achieved remarkable performance in single image super-resolution. However, recent studies on efficient super-resolution have mainly fo…
Recovering Continuous Scene Dynamics from A Single Blurry Image with Events
Zhangyi Cheng, Xiang Zhang, Lei Yu +3
This paper aims at demystifying a single motion-blurred image with events and revealing temporally continuous scene dynamics encrypted behind motion blurs. To achieve this end, an…
Learning to Super-Resolve Blurry Images with Events
Lei Yu, Bishan Wang, Xiang Zhang +4
Super-Resolution from a single motion Blurred image (SRB) is a severely ill-posed problem due to the joint degradation of motion blurs and low spatial resolution. In this paper, we…
Learning to See Through with Events
Lei Yu, Xiang Zhang, Wei Liao +2
Although synthetic aperture imaging (SAI) can achieve the seeing-through effect by blurring out off-focus foreground occlusions while recovering in-focus occluded scenes from multi…
Detecting Line Segments in Motion-blurred Images with Events
Huai Yu, Hao Li, Wen Yang +2
Making line segment detectors more reliable under motion blurs is one of the most important challenges for practical applications, such as visual SLAM and 3D reconstruction. Existi…
Fast Nearest Convolution for Real-Time Efficient Image Super-Resolution
Ziwei Luo, Youwei Li, Lei Yu +4
Deep learning-based single image super-resolution (SISR) approaches have drawn much attention and achieved remarkable success on modern advanced GPUs. However, most state-of-the-ar…
RFLA: Gaussian Receptive Field based Label Assignment for Tiny Object Detection
Chang Xu, Jinwang Wang, Wen Yang +3
Detecting tiny objects is one of the main obstacles hindering the development of object detection. The performance of generic object detectors tends to drastically deteriorate on t…
Detecting tiny objects in aerial images: A normalized Wasserstein distance and a new benchmark
Chang Xu, Jinwang Wang, Wen Yang +3
Tiny object detection (TOD) in aerial images is challenging since a tiny object only contains a few pixels. State-of-the-art object detectors do not provide satisfactory results on…
GLF-CR: SAR-Enhanced Cloud Removal with Global-Local Fusion
Fang Xu, Yilei Shi, Patrick Ebel +4
The challenge of the cloud removal task can be alleviated with the aid of Synthetic Aperture Radar (SAR) images that can penetrate cloud cover. However, the large domain gap betwee…
Learning to Extract Building Footprints from Off-Nadir Aerial Images
Jinwang Wang, Lingxuan Meng, Weijia Li +3
Extracting building footprints from aerial images is essential for precise urban mapping with photogrammetric computer vision technologies. Existing approaches mainly assume that t…
BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment
Ziwei Luo, Youwei Li, Shen Cheng +6
This work addresses the Burst Super-Resolution (BurstSR) task using a new architecture, which requires restoring a high-quality image from a sequence of noisy, misaligned, and low-…
Unifying Motion Deblurring and Frame Interpolation with Events
Xiang Zhang, Lei Yu
Slow shutter speed and long exposure time of frame-based cameras often cause visual blur and loss of inter-frame information, degenerating the overall quality of captured videos. T…
Deep Constrained Least Squares for Blind Image Super-Resolution
Ziwei Luo, Haibin Huang, Lei Yu +3
In this paper, we tackle the problem of blind image super-resolution(SR) with a reformulated degradation model and two novel modules. Following the common practices of blind SR, ou…
Autofocus for Event Cameras
Shijie Lin, Yinqiang Zhang, Lei Yu +3
Focus control (FC) is crucial for cameras to capture sharp images in challenging real-world scenarios. The autofocus (AF) facilitates the FC by automatically adjusting the focus se…
A Normalized Gaussian Wasserstein Distance for Tiny Object Detection
Jinwang Wang, Chang Xu, Wen Yang +1
Detecting tiny objects is a very challenging problem since a tiny object only contains a few pixels in size. We demonstrate that state-of-the-art detectors do not produce satisfact…
Motion Deblurring with Real Events
Fang Xu, Lei Yu, Bishan Wang +5
In this paper, we propose an end-to-end learning framework for event-based motion deblurring in a self-supervised manner, where real-world events are exploited to alleviate the per…
NTIRE 2021 Challenge on Burst Super-Resolution: Methods and Results
Goutam Bhat, Martin Danelljan, Radu Timofte +25
This paper reviews the NTIRE2021 challenge on burst super-resolution. Given a RAW noisy burst as input, the task in the challenge was to generate a clean RGB image with 4 times hig…
Event-based Synthetic Aperture Imaging with a Hybrid Network
Xiang Zhang, Wei Liao, Lei Yu +2
Synthetic aperture imaging (SAI) is able to achieve the see through effect by blurring out the off-focus foreground occlusions and reconstructing the in-focus occluded targets from…
ULSD: Unified Line Segment Detection across Pinhole, Fisheye, and Spherical Cameras
Hao Li, Huai Yu, Wen Yang +2
Line segment detection is essential for high-level tasks in computer vision and robotics. Currently, most stateof-the-art (SOTA) methods are dedicated to detecting straight line se…