Machine Learning Engineer
Joined June 2021
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StandardE2E 0.0.7 adds KIT MRT's KITScenes Multimodal & LongTail datasets plus a universal visualizer: any processed dataset to video, cameras + BEV, no per-dataset code.
github.com/stepankonev/Stand…
StandardE2E 0.0.6 adds three datasets: @torc_robotics's TruckDrive, @tudelft's View-of-Delft, and @motionaldrive's nuScenes — cameras, LiDAR, 3D boxes & HD maps, all through the same processing and unified PyTorch DataLoader.
github.com/stepankonev/Stand…
StandardE2E now supports @comma_ai 's comma2k19 dataset from 0.0.5 version: ~2,000 one-minute highway segments — front camera + ego trajectories — now load through the same processing and unified PyTorch DataLoader.
github.com/stepankonev/Stand…
Sharing what I've been working on: StandardE2E 🚗A unified API + PyTorch DataLoader for end-to-end AV datasets:
@Waymo (E2E + Perception), Argoverse 2, NAVSIM &
@wayve_ai Scenes101 and more WIP, all in one format. Less data plumbing, more model building!
github.com/stepankonev/Stand…
In WaterWatch.AI, we build a citizen science platform and autonomous boats that collect rich data about urban water quality. But collecting data is only the first step.
With @googlegemma 4, we transform it into compact, informative, and interactive actionable reports.
As part of the WaterWatch.ai project, we developed a small, affordable autonomous boat that, despite its size, can travel for miles and continuously collect water quality data. For more details, see the write-up: kaggle.com/competitions/gemm…
Just shipped something tiny I love💧
WaterWatch.ai — spot something off in an Amsterdam canal? Send a photo to a Telegram bot. #AI reads the photo, classifies the issue, pins it on a live public map. No app, no signup
#Amsterdam #grachten #citizenscience #water #ecology
Excited to share that I won a silver medal 🥈 at Kaggle Stanford Ribonanza RNA Folding competition 🧬(<-it is not RNA I know:) ! Thanks to all the organizers and participants for this enriching experience and the great opportunity!kaggle.com/competitions/stan…
Lately I became a prize winner of AISG-SLA Visual Localisation Challenge organized by @AISingapore with solutions presented at @IJCAIconf 23!
Announcement with brief solutions desc aisingapore.org/aisg-sla-vis…
This year @Waymo hosts Motion Prediction Challenge for the 3rd time. If you are a fan of autonomous driving you defenitely should participate! For your smooth start I share my prize winning solutions from previous years
⭐️ 21 lnkd.in/gEfgFaBq
⭐️ 22 lnkd.in/gqAAmGJM
21 [MotionCNN] github.com/stepankonev/Motio…
22 [MPA++] github.com/stepankonev/waymo…
steven konev retweeted
MPA: MultiPath++ Based Architecture for Motion Prediction
deepai.org/publication/mpa-m…
by @Konevsteven
#ComputerVision #PatternRecognition
steven konev retweeted
We've finally uploaded our report with winning solution at CVPR21 Autonomous Driving Workshop to arxiv!
MotionCNN: A Strong Baseline for Motion Prediction in Autonomous Driving
deepai.org/publication/motio…
by Stepan Konev et al. including @artsiom_s
#ConvolutionalNeuralNetwork #ComputerVision
I am proud to announce that this year I achieved the 3rd result on @Waymo Motion Prediction Challenge leaderboard (as of May, 26) and Honorable Mention.
The report is available on @CVPR Workshop on Autonomous Driving cvpr2022.wad.vision
The code is available on GitHub thread
The code of the solution github.com/stepankonev/waymo…
steven konev retweeted
Somehow my timeline is filled with papers where the models were trained with 64 A100 GPUs for weeks.
Grad students with two 2080Ti:
steven konev retweeted
I'm happy to announce that our team (me, @KonevSteven, K. Brodt) was awarded 3rd place within the Waymo Motion Prediction Challenge 🥳
Task: predict trajectories of the agents for 8 seconds into the future.
📜Technical report github.com/kbrodt/waymo-moti…
We also released our code ↓
steven konev retweeted
Waymo motion prediction challenge 2021: 3rd place solution.
⚒️Code github.com/kbrodt/waymo-moti…
