Sebastian Höfer

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Sebastian Höfer

Sebastian Höfer

@hoeferse

Manager of Applied Science @ Amazon Fulfillment Technologies & Robotics. Berliner. Opinions are my own.

Berlin, Deutschland Se unió Eylül 2013
329 Siguiendo408 Seguidores
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Sebastian Höfer
Sebastian Höfer@hoeferse·
Today we're announcing the release of "Kaputt", a breakthrough real world dataset for visual defect detection, 40x larger than SoTA. Spoiler: Even advanced AI models perform barely above random chance. Check out our blog post and paper #cv #iccv @ICCVConference @AmazonScience
Amazon Science@AmazonScience

Announcing Kaputt: a large-scale dataset for visual defect detection in retail logistics with 238,421 images across 48,376 unique items – 40x as large as current benchmarks:

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Anton Milan
Anton Milan@antonmil·
🚀 Get ready to build anomaly detection models that actually work in production! And win a share of $25,500 USD total prize pool! VAND 4.0 @CVPR 2026. Participate in the Kaputt2 Challenge! sites.google.com/view/vand4-cvp…
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alphaXiv
alphaXiv@askalphaxiv·
Introducing NotebookLM for arXiv papers 🚀 Transform dense AI research into an engaging conversation With context across thousands of related papers, it captures motivations, draws connections to SOTA, and explains key insights like a professor who's read the entire field
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Zipeng Fu
Zipeng Fu@zipengfu·
Mobile ALOHA's hardware is very capable. We brought it home yesterday and tried more tasks! It can: - do laundry👔👖 - self-charge⚡️ - use a vacuum - water plants🌳 - load and unload a dishwasher - use a coffee machine☕️ - obtain drinks from the fridge and open a beer🍺 - open doors🚪 - play with pets🐱 - throw away trash - turn on/off a lamp💡 Project website: mobile-aloha.github.io Co-lead @tonyzzhao, advised by @chelseabfinn (amazing photographing from @qingqing_zhao_ )
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Litian Liang
Litian Liang@litian_liang·
Introducing Robo360 dataset 🚀, the first real-world omnispective multi-view and multi-material robotic manipulation dataset. Robo360 captures synchronized multi-modal robot-object interaction data (video, audio, proprioception, control) to facilitate research in dynamic novel-view synthesis, robot learning, physics understanding, world models, and more! Code and data coming soon!
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Sebastian Höfer
Sebastian Höfer@hoeferse·
We're hiring! My science team at Amazon Fulfillment Technologies and Robotics in Berlin is hiring excellent scientists to work on visual defect detection models that see millions of images every day, delighting millions of customers. Apply! @AmazonScience amazon.jobs/en/jobs/252089…
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Anyi Rao
Anyi Rao@raoanyi·
Huge thanks and congrats to my coauthors @lvminzhang @magrawala #ControlNet for winning the Marr Prize /best paper award @ICCVConference #ICCV2023 Join us this afternoon at Oral 1:30 PM “Paris Sud” and Poster 2:30~4:30 PM “Foyer Sud 156”
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Sebastian Höfer
Sebastian Höfer@hoeferse·
Overwhelmingly inspiring experience at #ICCV2023 so far! I'm still available for coffee chats throughout the week, dont hesitate to drop me a PM. You can also catch me at the @AmazonScience booth starting 18:30 tonight!
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Sebastian Höfer@hoeferse·
What an inspiring day 1 at #ICCV2023! Alyosha Efros' talk at the Quo Vadis workshop was both entertaining and insightful. I'm open to coffee chats all week if you want to talk e.g. about data-centric AI, anomaly detection and science internships and opportunities at Amazon!
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Chan Hee (Luke) Song
Chan Hee (Luke) Song@luke_ch_song·
@hoeferse Hello! I am attending ICCV and would love to chat! Your dm is restricted to those with verified profile so couldn’t send one.
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Sebastian Höfer
Sebastian Höfer@hoeferse·
Bonjour Paris! I'll be attending ICCV the whole week, please drop me a PM if you'd like to have a chat! #iccv20
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Yann LeCun
Yann LeCun@ylecun·
DINOv2, the cutting-edge computer vision model trained through self-supervised learning to produce universal features, is now available under the Apache 2.0 license. Onward with open source AI.
AI at Meta@AIatMeta

Today we’re announcing two new updates in our computer vision work — a new, expanded license for our DINOv2 model and the release of FACET, a comprehensive new benchmark dataset to help evaluate and improve fairness in vision models. More details ➡️ bit.ly/3L35E1U 🧵

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