313 citations · 1.3k across the 32 of their papers we have counts for
33 papers
RUTA: Principled Visual Token Allocation via Rate-Utility Optimization
Jian Zou, Xiaoyu Xu, Zhihua Wang +3
High-resolution images and long videos provide vision-language models with rich context for multimodal reasoning and fine-grained perception, but the resulting long visual token se…
CachedSearch: Training-Free Cached Exploration for Test-Time Search in Video Diffusion
Shreshth Saini, Neil Birkbeck, Yilin Wang +2
Test-time search lets small video diffusion models rival larger ones, but costs 2-10x more. All candidates are fully denoised, although most are discarded. Training-free caching ma…
Subjective Portrait Region Cropping in Landscape Videos with Temporal Annotation Smoothing
Cheng-Han Lee, Maniratnam Mandal, Neil Birkbeck +3
With the rise of mobile video consumption on diverse handheld display resolutions and orientation modes, altering videos to aspect ratios poses challenges. Static cropping and bord…
LumaFlux: Lifting 8-Bit Worlds to HDR Reality with Physically-Guided Diffusion Transformers
Shreshth Saini, Hakan Gedik, Neil Birkbeck +3
The rapid adoption of HDR-capable devices has created a pressing need to convert the 8-bit Standard Dynamic Range (SDR) content into perceptually and physically accurate 10-bit Hig…
MDS-VQA: Model-Informed Data Selection for Video Quality Assessment
Jian Zou, Xiaoyu Xu, Zhihua Wang +3
Learning-based video quality assessment (VQA) has advanced rapidly, yet progress is increasingly constrained by a disconnect between model design and dataset curation. Model-centri…
Seeing Beyond 8bits: Subjective and Objective Quality Assessment of HDR-UGC Videos
Shreshth Saini, Bowen Chen, Neil Birkbeck +3
High Dynamic Range (HDR) user-generated (UGC) videos are rapidly proliferating across social platforms, yet most perceptual video quality assessment (VQA) systems remain tailored t…
Scaling Audio-Visual Quality Assessment Dataset via Crowdsourcing
Renyu Yang, Jian Jin, Lili Meng +4
Audio-visual quality assessment (AVQA) research has been stalled by limitations of existing datasets: they are typically small in scale, with insufficient diversity in content and…
TABES: Trajectory-Aware Backward-on-Entropy Steering for Masked Diffusion Models
Shreshth Saini, Avinab Saha, Balu Adsumilli +3
Masked Diffusion Models (MDMs) have emerged as a promising non-autoregressive paradigm for generative tasks, offering parallel decoding and bidirectional context utilization. Howev…
CHUG: Crowdsourced User-Generated HDR Video Quality Dataset
Shreshth Saini, Alan C. Bovik, Neil Birkbeck +2
High Dynamic Range (HDR) videos enhance visual experiences with superior brightness, contrast, and color depth. The surge of User-Generated Content (UGC) on platforms like YouTube…
Subjective and Objective Quality Assessment of Banding Artifacts on Compressed Videos
Qi Zheng, Li-Heng Chen, Chenlong He +6
Although there have been notable advancements in video compression technologies in recent years, banding artifacts remain a serious issue affecting the quality of compressed videos…
Context and Pixel Aware Large Language Model for Video Quality Assessment
Wen Wen, Yaohong Wu, Yue Sheng +3
Video quality assessment (VQA) is a challenging research topic with broad applications. Traditional hand-crafted and discriminative learning-based VQA models mainly focus on pixel-…
An Ensemble Approach to Short-form Video Quality Assessment Using Multimodal LLM
Wen Wen, Yilin Wang, Neil Birkbeck +1
The rise of short-form videos, characterized by diverse content, editing styles, and artifacts, poses substantial challenges for learning-based blind video quality assessment (BVQA…
YouTube SFV+HDR Quality Dataset
Yilin Wang, Joong Gon Yim, Neil Birkbeck +1
The popularity of Short form videos (SFV) has grown dramatically in the past few years, and has become a phenomenal video category with billions of viewers. Meanwhile, High Dynamic…
MRET: Multi-resolution Transformer for Video Quality Assessment
Junjie Ke, Tianhao Zhang, Yilin Wang +2
No-reference video quality assessment (NR-VQA) for user generated content (UGC) is crucial for understanding and improving visual experience. Unlike video recognition tasks, VQA ta…
CONVIQT: Contrastive Video Quality Estimator
Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2
Perceptual video quality assessment (VQA) is an integral component of many streaming and video sharing platforms. Here we consider the problem of learning perceptually relevant vid…
Making Video Quality Assessment Models Sensitive to Frame Rate Distortions
Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2
We consider the problem of capturing distortions arising from changes in frame rate as part of Video Quality Assessment (VQA). Variable frame rate (VFR) videos have become much mor…
Perceptual Quality Assessment of UGC Gaming Videos
Xiangxu Yu, Zhengzhong Tu, Neil Birkbeck +3
In recent years, with the vigorous development of the video game industry, the proportion of gaming videos on major video websites like YouTube has dramatically increased. However,…
Subjective and Objective Analysis of Streamed Gaming Videos
Xiangxu Yu, Zhenqiang Ying, Neil Birkbeck +3
The rising popularity of online User-Generated-Content (UGC) in the form of streamed and shared videos, has hastened the development of perceptual Video Quality Assessment (VQA) mo…
Image Quality Assessment using Contrastive Learning
Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2
We consider the problem of obtaining image quality representations in a self-supervised manner. We use prediction of distortion type and degree as an auxiliary task to learn featur…
High Frame Rate Video Quality Assessment using VMAF and Entropic Differences
Pavan C Madhusudana, Neil Birkbeck, Yilin Wang +2
The popularity of streaming videos with live, high-action content has led to an increased interest in High Frame Rate (HFR) videos. In this work we address the problem of frame rat…
MUSIQ: Multi-scale Image Quality Transformer
Junjie Ke, Qifei Wang, Yilin Wang +2
Image quality assessment (IQA) is an important research topic for understanding and improving visual experience. The current state-of-the-art IQA methods are based on convolutional…
Regression or Classification? New Methods to Evaluate No-Reference Picture and Video Quality Models
Zhengzhong Tu, Chia-Ju Chen, Li-Heng Chen +4
Video and image quality assessment has long been projected as a regression problem, which requires predicting a continuous quality score given an input stimulus. However, recent ef…
RAPIQUE: Rapid and Accurate Video Quality Prediction of User Generated Content
Zhengzhong Tu, Xiangxu Yu, Yilin Wang +3
Blind or no-reference video quality assessment of user-generated content (UGC) has become a trending, challenging, heretofore unsolved problem. Accurate and efficient video quality…
ST-GREED: Space-Time Generalized Entropic Differences for Frame Rate Dependent Video Quality Prediction
Pavan C. Madhusudana, Neil Birkbeck, Yilin Wang +2
We consider the problem of conducting frame rate dependent video quality assessment (VQA) on videos of diverse frame rates, including high frame rate (HFR) videos. More generally,…