Antonin Vobecky
@vobeckya.bsky.social
Ph.D. at CTU in Prague, multi-modal computer vision
supervised by Josef Sivic and Patrick Pérez
https://vobecant.github.io/
supervised by Josef Sivic and Patrick Pérez
https://vobecant.github.io/
Reposted by Antonin Vobecky
How to make your DINOv2 excel at dense in-context scene understanding tasks.
Check out DIP an effective post-training strategy by @ssirko.bsky.social @spyrosgidaris.bsky.social
@vobeckya.bsky.social @abursuc.bsky.social and Nicolas Thome 👇
#iccv2025
Check out DIP an effective post-training strategy by @ssirko.bsky.social @spyrosgidaris.bsky.social
@vobeckya.bsky.social @abursuc.bsky.social and Nicolas Thome 👇
#iccv2025
1/n 🚀New paper out - accepted at #ICCV2025!
Introducing DIP: unsupervised post-training that enhances dense features in pretrained ViTs for dense in-context scene understanding
Below: Low-shot in-context semantic segmentation examples. DIP features outperform DINOv2!
Introducing DIP: unsupervised post-training that enhances dense features in pretrained ViTs for dense in-context scene understanding
Below: Low-shot in-context semantic segmentation examples. DIP features outperform DINOv2!
June 25, 2025 at 7:35 PM
How to make your DINOv2 excel at dense in-context scene understanding tasks.
Check out DIP an effective post-training strategy by @ssirko.bsky.social @spyrosgidaris.bsky.social
@vobeckya.bsky.social @abursuc.bsky.social and Nicolas Thome 👇
#iccv2025
Check out DIP an effective post-training strategy by @ssirko.bsky.social @spyrosgidaris.bsky.social
@vobeckya.bsky.social @abursuc.bsky.social and Nicolas Thome 👇
#iccv2025
Reposted by Antonin Vobecky
MOCA ☕: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
by S. Gidaris, A. Bursuc, O. Simeoni, A. Vobecky, N. Komodakis, M. Cord, P. Pérez
Unify mask-and-predict & contrastive SSL objectives -> better performance w/ 3x faster training
by S. Gidaris, A. Bursuc, O. Simeoni, A. Vobecky, N. Komodakis, M. Cord, P. Pérez
Unify mask-and-predict & contrastive SSL objectives -> better performance w/ 3x faster training
April 9, 2025 at 9:38 AM
MOCA ☕: Self-supervised Representation Learning by Predicting Masked Online Codebook Assignments
by S. Gidaris, A. Bursuc, O. Simeoni, A. Vobecky, N. Komodakis, M. Cord, P. Pérez
Unify mask-and-predict & contrastive SSL objectives -> better performance w/ 3x faster training
by S. Gidaris, A. Bursuc, O. Simeoni, A. Vobecky, N. Komodakis, M. Cord, P. Pérez
Unify mask-and-predict & contrastive SSL objectives -> better performance w/ 3x faster training