Bibliographic record
Abstract
Welcome to the 2017 Proceedings of the Eurographics Symposium on Rendering!This is the 28th edition of the conference, which is a premier venue for research in rendering and related areas.This year's conference is held in Helsinki, Finland on 19-21 June 2017, and co-located with the Workshop on Material Appearance Modeling.We look forward to welcoming researchers eager to meet and discuss the various areas and applications of rendering.As in earlier years, EGSR 2017 offers two submission tracks.The traditional "CGF track", with papers that are reviewed for publication in Computer Graphics Forum, is accompanied by an "Experimental Ideas and Implementation" (EI&I) track.The latter targets submissions with fresh ideas, algorithmic details, or best-practice solutions that might still require further validation, but that would be inspiring for the community.We received a total of 74 abstract submissions (53 in the CGF track and 21 in the EI&I track).After some withdrawals in the CGF track, we had a total of 41 full CGF paper submissions for review.The IPC accepted 16 full CGF papers and 12 EI&I papers for a total of 28 papers (two more than in 2016).In addition, we offered invitations to three CGF papers to be presented in our program.Thus, we will have a total of 31 presentations in an exciting and packed 2.5-day event.In addition to the paper talks, our program includes two great keynote talks given by Prof. Ren Ng from UC Berkeley and Prof. Kun Zhou from Zhejiang University.We are very excited to hear about their latest work and thank them for accepting our invitation to present at EGSR.We would like to thank both the authors for the high quality of the submitted papers as well as the IPC members for their great effort during this very tight multi-stage review process.We have kept the review process the same as in the previous years, with three IPC reviewers per paper submission.Some of the papers rejected to CGF track were given the opportunity to present in the EI&I track.We further thank Stefanie Behnke for her tremendous help in producing the EGSR proceedings, and for very quickly addressing a variety of unexpected issues that came up at different times throughout.We are very grateful to be able to count on her during the entire process.Additionally, we would like to thank Min Chen, Editor in Chief of CGF, for helping us cover all aspects of the journal publication process and for giving support for inviting the additional CGF papers to the conference.We would like to express our gratitude to our local organizers Jaakko Lehtinen, Samuli Laine, and Timo Aila for the tremendous work required to put the event together.We are looking forward to a great three days in Helsinki.Thanks guys!Finally, we thank the steering committee of the Eurographics Working Group on Rendering for inviting us as paper's chairs.We hope to be able to complete this cycle in Helsinki having contributed to maintaining the high quality level of research output of our rendering family.Let us all (sur)render ourselves to three exciting days in Helsinki!
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.009 | 0.005 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.938 | 0.921 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".