🔥 Can in-context segmentation emerge directly from frozen DINOv3 features? At #CVPR2026, we present INSID3: Training-Free In-Context Segmentation with DINOv3 — a collaboration between PoliTo, TU Darmstadt and TU Munich. Check it out: github.com/visinf/INSID3
🚀 As #CVPR2025 week kicks off, meet SANSA: Semantically AligNed Segment Anything 2 We turn SAM2 into a semantic few-shot segmenter: 🧠 Unlocks latent semantics in frozen SAM2 ✏️ Supports any prompt: fast and scalable annotation 📦 No extra encoders 📎 github.com/ClaudiaCutta...
To Match or Not to Match: Revisiting Image Matching for Reliable Visual Place Recognition Davide Sferrazza, @berton-gabri.bsky.social Gabriele Trivigno, Carlo Masone tl;dr: global descriptors nowadays are often better than local feature matching methods for simple datasets. arxiv.org/abs/2504.06116
🔥 Our paper SAMWISE: Infusing Wisdom in SAM2 for Text-Driven Video Segmentation is accepted as a #Highlight at #CVPR2025! 🎉 We make #SegmentAnything wiser, enabling it to understand textual prompts—training only 4.9M parameters! 🧠 💻 Code, models & demo: github.com/ClaudiaCutta... Why SAMWISE?👇
To Match or Not to Match: Revisiting Image Matching for Reliable Visual Place Recognition Davide Sferrazza, @berton-gabri.bsky.social, @gabtriv.bsky.social, Carlo Masone tl;dr:VPR datasets saturate;re-ranking not good;image matching->uncertainty->inlier counts->confidence arxiv.org/abs/2504.06116
🚀 Paper Release! 🚀 Curious about image retrieval and contrastive learning? We present: 📄 "All You Need to Know About Training Image Retrieval Models" 🔍 The most comprehensive retrieval benchmark—thousands of experiments across 4 datasets, dozens of losses, batch sizes, LRs, data labeling, and more!
Trying to convince my bluesky feed to put me in the Computer Vision community. Right now I only see posts about the orange-haired president. @berton-gabri.bsky.social @gabrigole.bsky.social how did you do it?
Image segmentation doesn’t have to be rocket science. 🚀 Why build a rocket engine full of bolted-on subsystems when one elegant unit does the job? 💡 That’s what we did for segmentation. ✅ Meet the Encoder-only Mask Transformer (EoMT): tue-mps.github.io/eomt (CVPR 2025) (1/6)
