New Light Field Image Dataset

By M. Rerábek, Touradj Ebrahimi. International Workshop on Quality of Multimedia Experience, 2016

389 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/e4798c9fbe160382940d3591f6364c3eea15c9f8

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Zhen Cheng
2. Gaochang Wu
3. Qionghai Dai
4. Zhiwei Xiong
5. Yebin Liu
6. Belén Masiá
7. Zhengjun Zha
8. Chang Wen Chen

Citations in the corpus

• Light Field Super-Resolution with Zero-Shot Learning (2021, background): “The target datasets include Stanford Lytro Archive (Stan) [28], EPFL [29], HCI old (HCI1) [42], and HCI new (HCI2) [11].”
• A Dataset and Evaluation Methodology for Depth Estimation on 4D Light Fields (2016, background): “We are aware of multiple smaller and larger collections, in particular the Stanford Light Field Archive [8], the Synthetic Light Field Archive [9], a collection of Lytro images [10], the 3D High-Resolution Disney Dataset [11], and the New Light Field Image Dataset [12].”
• Light Field Image Processing: An Overview (2017, background): “Reˇr´abek and Ebrahimi [275] also provided 118 light fields captured with a Lytro camera [4].”