Olaf Dünkel
@oduenkel.bsky.social
📤 45
📥 77
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ELLIS PhD @ MPI & Oxford - Generative Models for Vision
https://odunkel.github.io/
pinned post!
Are you using DINOv2 for tasks that require semantic features? DIY-SC might be the alternative! It refines DINOv2 or SD+DINOv2 features and achieves a new SOTA on the semantic correspondence dataset SPair-71k when not relying on annotated keypoints! [1/6]
genintel.github.io/DIY-SC
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7 months ago
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Arrived in San Diego for
#NeurIPS2025
! Reach out if you are around too! Happy to chat! We'll present AttentionChains on Thursday afternoon!
neurips.cc/virtual/2025...
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NeurIPS Poster Attention (as Discrete-Time Markov) ChainsNeurIPS 2025
https://neurips.cc/virtual/2025/loc/san-diego/poster/115284
about 1 month ago
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Currently travelling to
#ICCV2025
and looking forward to presenting DIY-SC and CNS-Bench there! DIY-SC: #538 at poster session 2 CNS-Bench: #1839 at poster session 5 Happy to chat during the poster sessions or at some other time if you are around!
3 months ago
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reposted by
Olaf Dünkel
Thomas Wimmer
3 months ago
Super excited to introduce ✨ AnyUp: Universal Feature Upsampling 🔎 Upsample any feature - really any feature - with the same upsampler, no need for cumbersome retraining. SOTA feature upsampling results while being feature-agnostic at inference time. 🌐
wimmerth.github.io/anyup/
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You read this? You’ll likely read the linked post too. You like it? Your followers might see it too. In other words: Attention here → attention to Yotam’s post. We explore how transformer attention can be propagated—like PageRank, but for attention. Fun work with
@yotamerel.bsky.social
add a skeleton here at some point
6 months ago
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Are you using DINOv2 for tasks that require semantic features? DIY-SC might be the alternative! It refines DINOv2 or SD+DINOv2 features and achieves a new SOTA on the semantic correspondence dataset SPair-71k when not relying on annotated keypoints! [1/6]
genintel.github.io/DIY-SC
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7 months ago
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