activity
20162023
most citedHybrid Loss for Learning Single-Image-based HDR Reconstruction

18 citations · 63 across the 8 of their papers we have counts for

collaborators
Showing cs.CVShow all

21 papers · 1 filter

cs.CV20221 cited

GTAV-NightRain: Photometric Realistic Large-scale Dataset for Night-time Rain Streak Removal

Fan Zhang, Shaodi You, Yu Li +1

Rain is transparent, which reflects and refracts light in the scene to the camera. In outdoor vision, rain, especially rain streaks degrade visibility and therefore need to be remo…

cs.CV202215 cited

Multitask AET with Orthogonal Tangent Regularity for Dark Object Detection

Ziteng Cui, Guo-Jun Qi, Lin Gu +3

Dark environment becomes a challenge for computer vision algorithms owing to insufficient photons and undesirable noise. To enhance object detection in a dark environment, we propo…

cs.CV20212 cited

Finding a Needle in a Haystack: Tiny Flying Object Detection in 4K Videos using a Joint Detection-and-Tracking Approach

Ryota Yoshihashi, Rei Kawakami, Shaodi You +3

Detecting tiny objects in a high-resolution video is challenging because the visual information is little and unreliable. Specifically, the challenge includes very low resolution o…

cs.CV2020

Weakly-supervised Semantic Segmentation in Cityscape via Hyperspectral Image

Yuxing Huang, Shaodi You, Ying Fu +1

High-resolution hyperspectral images (HSIs) contain the response of each pixel in different spectral bands, which can be used to effectively distinguish various objects in complex…

cs.CV2020

Kinship Identification through Joint Learning Using Kinship Verification Ensembles

Wei Wang, Shaodi You, Sezer Karaoglu +1

Kinship verification is a well-explored task: identifying whether or not two persons are kin. In contrast, kinship identification has been largely ignored so far. Kinship identific…

cs.CV2020

Feedback Graph Convolutional Network for Skeleton-based Action Recognition

Hao Yang, Dan Yan, Li Zhang +4

Skeleton-based action recognition has attracted considerable attention in computer vision since skeleton data is more robust to the dynamic circumstance and complicated background…