End of Round 2⏱️

Round 2 of Food Recognition Benchmark has ended !! :rocket:

This round saw a lot more activity and a lot more rank swaps on the leaderboard.
Thanks to you all for making it a success. :raised_hands:

While a few of submissions are being re-evaluated at the moment, the public leaderboard looks like this right now:

The number of participants who crossed the official baseline has increased from 12 to 15.
At the same time, participants having score >= 0.200 AP is increased from 6 to 11 as well! :partying_face:

We can’t wait to complete the due diligence before making the winners’ announcement.
Stay tuned for it! :loudspeaker:


Why Food Recognition Benchmark matters?

It’s a good time to re-share about exciting updates on how the community collaboration has worked so far and what it’s enabling! [Blog Post]

The Food Recognition Benchmark is not a competition, but an ongoing collaboration with a community of inspiring individuals like yourself, to deliver the future of diet tracking in research cohorts around the world.


What can you do meanwhile?

:handshake: Start some interesting discussions with other challenge participants’ here on the Forums or on Discord Chat.
:wink: Share what worked and what didn’t during the competition. And maybe some interesting approaches you may want to try out in future?
:ear: Share any feedbacks you have for future Rounds either in this thread of here.
:speak_no_evil: Guess the winners in this thread

3 Likes

Great work guys.
Thank you @mohanty, @shivam for making this challenge happen.
Thanks everyone on the leaderboard, it was really fun this time. In the previous week it felt like a roller coaster ride with all the score shuffling. I expect the final leaderboard will see a very small variance in the score and the results don’t shuffle by a huge gap.
Congratulations to @team_zi, and great work @saidinesh_pola, @nivedita_rufus and @unnikrishnan.r

5 Likes

Thanks for hosting this challenge. Will you be releasing the winners source code? Would love to learn how I can improve my model.

1 Like

Hi, yes. :raised_hands:

As per the challenge rules:

image

We look forward to the top solutions being shared with the community - you should hear more on this in further winner announcements!

Thanks to Aicrowd for hosting this yearly competition and benchmark. It was a lot of fun working on it, exploring and learning models for instance segmentation for solving the task on food recognition.
Thanks for my teammates for this work.
Thanks @shivam for a lot of helping us with aicrowd infrastructure, @gaurav_singhal for your paper on your previous year best approach and unbelievable race on score :slight_smile: other participants for good time within this competition!
Also, congratulations to @gaurav_singhal and @Camaro!!!

2 Likes

Thanks, @Mykola_Lavreniuk. I hope our techniques are different from each other to broaden our knowledge horizons. I would love to collaborate with you and your team if I will be invited to co-author.
Congratulation to @Lab_zi and @Camaro

2 Likes

Thanks, looking forward to the source code being posted!