48 citations · 92 across the 14 of their papers we have counts for
15 papers
DRIFT: Deep Restoration, ISP Fusion, and Tone-mapping
Soumendu Majee, Joshua Peter Ebenezer, Abhinau K. Venkataramanan +6
Smartphone cameras have gained immense popularity with the adoption of high-resolution and high-dynamic range imaging. As a result, high-performance camera Image Signal Processors…
GenMFSR: Generative Multi-Frame Image Restoration and Super-Resolution
Harshana Weligampola, Joshua Peter Ebenezer, Weidi Liu +4
Camera pipelines receive raw Bayer-format frames that need to be denoised, demosaiced, and often super-resolved. Multiple frames are captured to utilize natural hand tremors and en…
MFSR-GAN: Multi-Frame Super-Resolution with Handheld Motion Modeling
Fadeel Sher Khan, Joshua Ebenezer, Hamid Sheikh +1
Smartphone cameras have become ubiquitous imaging tools, yet their small sensors and compact optics often limit spatial resolution and introduce distortions. Combining information…
HDR or SDR? A Subjective and Objective Study of Scaled and Compressed Videos
Joshua P. Ebenezer, Zaixi Shang, Yixu Chen +4
We conducted a large-scale study of human perceptual quality judgments of High Dynamic Range (HDR) and Standard Dynamic Range (SDR) videos subjected to scaling and compression leve…
HDR-ChipQA: No-Reference Quality Assessment on High Dynamic Range Videos
Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu +3
We present a no-reference video quality model and algorithm that delivers standout performance for High Dynamic Range (HDR) videos, which we call HDR-ChipQA. HDR videos represent w…
Making Video Quality Assessment Models Robust to Bit Depth
Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu +3
We introduce a novel feature set, which we call HDRMAX features, that when included into Video Quality Assessment (VQA) algorithms designed for Standard Dynamic Range (SDR) videos,…
A subjective study of the perceptual acceptability of audio-video desynchronization in sports videos
Joshua Peter Ebenezer
This paper presents the results of a study conducted on the perceptual acceptability of audio-video desynchronization for sports videos. The study was conducted with 45 videos gene…
Subjective Assessment of High Dynamic Range Videos Under Different Ambient Conditions
Zaixi Shang, Joshua P. Ebenezer, Alan C. Bovik +3
High Dynamic Range (HDR) videos can represent a much greater range of brightness and color than Standard Dynamic Range (SDR) videos and are rapidly becoming an industry standard. H…
Subjective and Objective Quality Assessment of High-Motion Sports Videos at Low-Bitrates
Joshua P. Ebenezer, Yixu Chen, Yongjun Wu +2
Videos often have to be transmitted and stored at low bitrates due to poor network connectivity during adaptive bitrate streaming. Designing optimal bitrate ladders that would sele…
ChipQA: No-Reference Video Quality Prediction via Space-Time Chips
Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu +3
We propose a new model for no-reference video quality assessment (VQA). Our approach uses a new idea of highly-localized space-time (ST) slices called Space-Time Chips (ST Chips).…
Assessment of Subjective and Objective Quality of Live Streaming Sports Videos
Zaixi Shang, Joshua P. Ebenezer, Alan C. Bovik +3
Video live streaming is gaining prevalence among video streaming services, especially for the delivery of popular sporting events. Many objective Video Quality Assessment (VQA) mod…
Detection of Audio-Video Synchronization Errors Via Event Detection
Joshua P. Ebenezer, Yongjun Wu, Hai Wei +2
We present a new method and a large-scale database to detect audio-video synchronization(A/V sync) errors in tennis videos. A deep network is trained to detect the visual signature…
No-Reference Video Quality Assessment Using Space-Time Chips
Joshua P. Ebenezer, Zaixi Shang, Yongjun Wu +2
We propose a new prototype model for no-reference video quality assessment (VQA) based on the natural statistics of space-time chips of videos. Space-time chips (ST-chips) are a ne…
Single Image Haze Removal Using Conditional Wasserstein Generative Adversarial Networks
Joshua Peter Ebenezer, Bijaylaxmi Das, Sudipta Mukhopadhyay
We present a method to restore a clear image from a haze-affected image using a Wasserstein generative adversarial network. As the problem is ill-conditioned, previous methods have…
Automatic segmentation of skin lesions using deep learning
Joshua Peter Ebenezer, Jagath C. Rajapakse
This paper summarizes the method used in our submission to Task 1 of the International Skin Imaging Collaboration's (ISIC) Skin Lesion Analysis Towards Melanoma Detection challenge…