From the 1 of 8 linked papers with an AI index.
8 papers
Evaluating VLMs for Autonomous Agent-Driven Geometry Clipping Detection in Video Game QA
Carlos Celemin, Benedict Wilkins, Adrián Barahona-RÃos +2
The paper evaluates several recent vision‑language models as zero‑shot detectors for geometry‑clipping bugs in video games, using an autonomous agent to collect frames and automati…
TempGlitch: Evaluating Vision-Language Models for Temporal Glitch Detection in Gameplay Videos
Yakun Yu, Ashley Wiens, Adrián Barahona-RÃos +4
Vision-language models (VLMs) are increasingly being explored for video game quality assurance, especially gameplay glitch detection. Most existing evaluations, however, treat glit…
RESP: Reference-guided Sequential Prompting for Visual Glitch Detection in Video Games
Yakun Yu, Ashley Wiens, Adrián Barahona-RÃos +4
Visual glitches in video games degrade player experience and perceived quality, yet manual quality assurance cannot scale to the growing test surface of modern game development. Pr…
VideoGameQA-Bench: Evaluating Vision-Language Models for Video Game Quality Assurance
Mohammad Reza Taesiri, Abhijay Ghildyal, Saman Zadtootaghaj +2
With video games now generating the highest revenues in the entertainment industry, optimizing game development workflows has become essential for the sector's sustained growth. Re…
Non-Aligned Reference Image Quality Assessment for Novel View Synthesis
Abhijay Ghildyal, Rajesh Sureddi, Nabajeet Barman +2
Evaluating the perceptual quality of Novel View Synthesis (NVS) images remains a key challenge, particularly in the absence of pixel-aligned ground truth references. Full-Reference…
TRIQA: Image Quality Assessment by Contrastive Pretraining on Ordered Distortion Triplets
Rajesh Sureddi, Saman Zadtootaghaj, Nabajeet Barman +1
Image Quality Assessment (IQA) models aim to predict perceptual image quality in alignment with human judgments. No-Reference (NR) IQA remains particularly challenging due to the a…