activity
20152021
most citedKindling the Darkness: A Practical Low-light Image Enhancer

84 citations · 141 across the 8 of their papers we have counts for

collaborators

9 papers

cs.HC20211 cited

Towards Visual Explainable Active Learning for Zero-Shot Classification

Shichao Jia, Zeyu Li, Nuo Chen +1

Zero-shot classification is a promising paradigm to solve an applicable problem when the training classes and test classes are disjoint. Achieving this usually needs experts to ext…

cs.CV201916 cited

Dunhuang Grottoes Painting Dataset and Benchmark

Tianxiu Yu, Shijie Zhang, Cong Lin +5

This document introduces the background and the usage of the Dunhuang Grottoes Dataset and the benchmark. The documentation first starts with the background of the Dunhuang Grotto,…

cs.CV20192 cited

OVSNet : Towards One-Pass Real-Time Video Object Segmentation

Peng Sun, Peiwen Lin, Guangliang Cheng +3

Video object segmentation aims at accurately segmenting the target object regions across consecutive frames. It is technically challenging for coping with complicated factors (e.g.…

cs.CV201984 cited

Kindling the Darkness: A Practical Low-light Image Enhancer

Yonghua Zhang, Jiawan Zhang, Xiaojie Guo

Images captured under low-light conditions often suffer from (partially) poor visibility. Besides unsatisfactory lightings, multiple types of degradations, such as noise and color…

cs.CV2019

Single Image Deraining: A Comprehensive Benchmark Analysis

Siyuan Li, Iago Breno Araujo, Wenqi Ren +7

We present a comprehensive study and evaluation of existing single image deraining algorithms, using a new large-scale benchmark consisting of both synthetic and real-world rainy i…

cs.CV201935 cited

PFLD: A Practical Facial Landmark Detector

Xiaojie Guo, Siyuan Li, Jinke Yu +5

Being accurate, efficient, and compact is essential to a facial landmark detector for practical use. To simultaneously consider the three concerns, this paper investigates a neat m…