Sophia Sirko-Galouchenko 🇺🇦

@ssirko.bsky.social

PhD student in visual representation learning at Valeo.ai and Sorbonne Université (MLIA)

1/n New paper - V-GIFT 🎁 Self-supervised tasks like rotation prediction or colorization were big in 2018. Do they still matter? Yes. We turn them into visual instruction tuning data for MLLMs. Result: models rely more on the image and perform better on vision tasks 👀

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Need pixel-level features from your backbone (DINOv3, CLIP, RADIO, FRANCA...)? 🚀Introducing NAF: A universal, zero-shot feature upsampler. It turns low-res ViT features into pixel-perfect maps. -⚡ Model-agnostic -🥇 SoTA results -🚀 4× faster than SoTA -📈 Scales up to 2K res

🚗🌐 Working on domain adaptation for 3D point clouds / LiDAR? We'll present MuDDoS at BMVC: a method that boosts multimodal distillation for 3D semantic segmentation under domain shift. 📍 BMVC 🕚 Monday, Poster Session 1: Multimodal Learning (11:00–12:30) 📌 Hadfield Hall #859

🎉 Accepted papers at NeurIPS 2025 🎉 The team is proud to announce that several paper were accepted at #NeurIPS25. Looking forward to meet in Paris (25th-26th Nov), Copenhagen or San Diego (1st-7th Dec)! Let's present our papers ⬇️

Come say hi to our poster October 21st at 11:45 poster session 1 (#399)! We introduce unsupervised post-training of ViTs that enhances dense features for in-context tasks. First conference as a PhD student, really excited to meet new people.

Sophia Sirko-Galouchenko 🇺🇦@ssirko.bsky.social · last yr.

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!