🍕 Upsample Anything 🍕

👉Upsample Anything, a novel universal, training-free up-sampler via lightweight test-time optimization. No code but it's a relevant paper💙

👉Review https://t.ly/7LE6G
👉Paper https://lnkd.in/dsUfdtih

🦞Single Synthetic Image per Class🦞

👉MIT unveils Linear Gradient Matching (H/T Torralba), a novel method of distillation to use a single synthetic image per class for linear classifiers training (and more). Repo available💙

👉Review https://t.ly/dD3un
👉Paper arxiv.org/pdf/2511.16674
👉Project linear-gradient-matching.github.io/
👉Repo github.com/GeorgeCazenavette/linear-gradient-matching

🧪 EfficientSAM3 is out 🧪

👉Bristol announces EfficientSAM3, a family of efficient models built on Progressive Hierarchical Distillation that transfers capability from SAM3 to lightweight students. Code coming (in sync with SAM3 release)💙

👉Review https://t.ly/bfXP2
👉Paper arxiv.org/pdf/2511.15833
👉Project simonzeng7108.github.io/efficientsam3/
👉Repo github.com/SimonZeng7108/efficientsam3

🌩️ Cloud4D in time 🌩️

👉Cloud4D: physically-realistic 3D cloud fields using ground-based cameras at a 25 m spatial resolution and 5 s temporal resolution. Repo coming, Data released💙

👉Review https://t.ly/w7Zly
👉Paper arxiv.org/pdf/2511.19431
👉Project cloud4d.jacob-lin.com/
👉Data https://drive.google.com/drive/folders/1QU_0kIUXIVt8h3uqygBeaF3Gvr_L5SdX?usp=drive_link
👉Repo TBA