19 citations · 53 across the 8 of their papers we have counts for
10 papers
GameScope: A Multi-Attribute, Multi-Codec Benchmark Dataset for Gaming Video Quality Assessment
Rajesh Sureddi, Shreshth Saini, Avinab Saha +1
The development of video game streaming has grown rapidly, with major platforms such as YouTube and Twitch using different codecs. To support quality assessment models that work co…
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…
Learning Perceptual Representations for Gaming NR-VQA with Multi-Task FR Signals
Yu-Chih Chen, Michael Wang, Chieh-Dun Wen +4
No-reference video quality assessment (NR-VQA) for gaming videos is challenging due to limited human-rated datasets and unique content characteristics including fast motion, styliz…
Focus-N-Fix: Region-Aware Fine-Tuning for Text-to-Image Generation
Xiaoying Xing, Avinab Saha, Junfeng He +9
Text-to-image (T2I) generation has made significant advances in recent years, but challenges still remain in the generation of perceptual artifacts, misalignment with complex promp…
Subjective and Objective Quality Assessment of Rendered Human Avatar Videos in Virtual Reality
Yu-Chih Chen, Avinab Saha, Alexandre Chapiro +6
We study the visual quality judgments of human subjects on digital human avatars (sometimes referred to as "holograms" in the parlance of virtual reality [VR] and augmented reality…
Exploring Explainability in Video Action Recognition
Avinab Saha, Shashank Gupta, Sravan Kumar Ankireddy +2
Image Classification and Video Action Recognition are perhaps the two most foundational tasks in computer vision. Consequently, explaining the inner workings of trained deep neural…
HIDRO-VQA: High Dynamic Range Oracle for Video Quality Assessment
Shreshth Saini, Avinab Saha, Alan C. Bovik
We introduce HIDRO-VQA, a no-reference (NR) video quality assessment model designed to provide precise quality evaluations of High Dynamic Range (HDR) videos. HDR videos exhibit a…
Re-IQA: Unsupervised Learning for Image Quality Assessment in the Wild
Avinab Saha, Sandeep Mishra, Alan C. Bovik
Automatic Perceptual Image Quality Assessment is a challenging problem that impacts billions of internet, and social media users daily. To advance research in this field, we propos…
Study of Subjective and Objective Quality Assessment of Mobile Cloud Gaming Videos
Avinab Saha, Yu-Chih Chen, Chase Davis +5
We present the outcomes of a recent large-scale subjective study of Mobile Cloud Gaming Video Quality Assessment (MCG-VQA) on a diverse set of gaming videos. Rapid advancements in…
GAMIVAL: Video Quality Prediction on Mobile Cloud Gaming Content
Yu-Chih Chen, Avinab Saha, Chase Davis +5
The mobile cloud gaming industry has been rapidly growing over the last decade. When streaming gaming videos are transmitted to customers' client devices from cloud servers, algori…