You can find the survey by Adam Bargteil here.
I have a simpler proposal: revert to the original conference format for SIGGRAPH technical papers (i.e., before year 2002) and give authors the option to submit an extended version of their SIGGRAPH conference papers to ToG as journal papers (with the usual rule of at least 30\% more new materials, for example, most likely for additional analysis and evaluation).
We can then get rid of the current special ToG issues of SIGGRAPH and SIGGRAPH Asia.
I heard from this podcast about how Dr. Cecilia Conrad was advised to, instead of making her lectures too clear, “fill the board with calculus” to establish her credential for students who thought she was an “affirmative action hire”.
I know plenty people, my past self included, who are natural board-calculus fillers by overwhelming technical communications such as research papers and presentations with math/algorithm details, and need to reverse what Dr. Cecilia Conrad did.
After 30+ timed-model-drawing sessions my sketches still have only forms but not actions/gestures, which I realized is caused by mimicking what I see but without really understanding.
Specifically, the first lesson of my first drawing training is to draw exactly what I see so that the mind won’t get in the way, but now I need to get my mind back into the process.
(I was so frustrated that I did a few visceral physical drawings for mental balance.)
The quote “you draw with your mind not your hand” from the Vilppu drawing manual (which is a great book not just for drawing) reminded me of what Stephen King said in the gunslinger:
I do not aim with my hand; he who aims with his hand has forgotten the face of his father.
I aim with my eye.I do not shoot with my hand; he who shoots with his hand has forgotten the face of his father.
I shoot with my mind.I do not kill with my gun; he who kills with his gun has forgotten the face of his father.
I kill with my heart.
Looking at this dithering technique today brought back memories of my previous work on blue noise sampling and the associative life, almost like traveling back in time.
Here is my (somehow tongue-in-the-cheek) comparison of the 3 venues:
SIGGRAPH – this paper presents the best invention since the fire, the wheel, the electricity, the internet, etc.
CHI – 2 pages of technical content + 8 pages of user study.
UIST – somewhere in between, no time for conducting/claiming too much user study or technical novelty.
I dreamed about this logo of an ongoing project among existing Adobe apps.
Does this problem require ML, or a hand-crafted method would be better (to control, debug, understand, implement, etc.)?
Is this better for a paper or just open source?
How did you come up with the architecture, and why?
What I like to see in everything machine-learning paper:
Does this problem require ML, or a hand-crafted method would be better (to control, debug, understand, implement, etc.)?
Is this better for a paper or just open source?
How did you come up with the architecture, and why?
— Li-Yi Wei (@liyiwei) February 15, 2021
How people came up with their ideas!
What I most want to know about but is least described in research papers: pic.twitter.com/PVI8ur97Bf
— Li-Yi Wei (@liyiwei) November 27, 2020
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