Summary of Gta-hdr: a Large-scale Synthetic Dataset For Hdr Image Reconstruction, by Hrishav Bakul Barua et al.
GTA-HDR: A Large-Scale Synthetic Dataset for HDR Image Reconstruction
by Hrishav Bakul Barua, Kalin Stefanov, KokSheik Wong, Abhinav Dhall, Ganesh Krishnasamy
First submitted to arxiv on: 26 Mar 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Graphics (cs.GR); Machine Learning (cs.LG); Multimedia (cs.MM); Image and Video Processing (eess.IV)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The paper introduces GTA-HDR, a large-scale synthetic dataset of photo-realistic High Dynamic Range (HDR) images generated from the Grand Theft Auto V (GTA-V) video game. This dataset addresses the lack of benchmarking datasets for HDR image reconstruction and related computer vision tasks, such as 3D human pose estimation, human body part segmentation, and holistic scene segmentation. The authors evaluate the proposed dataset, demonstrating significant improvements over state-of-the-art HDR image reconstruction methods in both qualitative and quantitative assessments. The GTA-HDR dataset, data collection pipeline, and evaluation code are made available for further research. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine being able to take amazing photos or videos with super bright colors and details that show up really well. That’s what High Dynamic Range (HDR) is all about! But right now, capturing HDR content from real-life scenes is really hard and takes a lot of time and money. So, scientists are trying to figure out how to make HDR images from lower-quality pictures. To help with this problem, the researchers in this paper created a huge dataset of fake but realistic HDR images using a popular video game called GTA-V. They tested their dataset and showed that it’s way better than what’s currently available for things like recognizing people or objects in videos. |
Keywords
* Artificial intelligence * Pose estimation
