🍕 Superpixel Anything (SOTA) 🍕

👉 SuperPixel Anything Model, a versatile framework for segmenting images. Extracting image features for superpixel generation blended with a large-scale pretrained model for semantic-agnostic segmentation to ensure superpixels alignement with masks. Damn romantic. Repo & Dataset available💙

👉Review https://t.ly/rpxRh
👉Paper arxiv.org/pdf/2509.12791
👉Repo github.com/waldo-j/spam

👽DAM for SAM2 Tracking👽

👉From the University of Ljubljana a novel distractor-aware drop-in memory module for SAM2. Reducing the tracking drift toward distractors and improves redetection capability after object occlusions. DAM4SAM outperforms SAM2.1, SOTA on 10 benchmarks. Repo released 💙

👉Review https://t.ly/8aR59
👉Paper https://arxiv.org/pdf/2509.13864
👉Project jovanavidenovic.github.io/dam-4-sam/
👉Repo github.com/jovanavidenovic/DAM4SAM

🔥🔥 It's time to decide whether you want to give LinkedIn your data for AI training or not 🔥🔥

Poll: https://lnkd.in/p/ddnenZgH

Set here: https://linkedin.com/mypreferences/d/settings/data-for-ai-improvement

🐳 Invariant Saliency Detection 🐳

👉SI-SOD: invariant salient object detection in scenarios when multiple salient objects of significantly different sizes appear within a single image. Repo released💙

👉Review https://lnkd.in/p/dZBfbSsf
👉Paper https://arxiv.org/pdf/2509.15573
👉Project https://ferry-li.github.io/SI_SOD/
👉Repo https://github.com/Ferry-Li/SI-SOD

🫓 WINNER of LSVOS Challenge 🫓

👉SaSaSa2VA introduces Segmentation Augmentation to improve global video understanding while remaining efficient, and employs Selective Averaging at inference to robustly fuse complementary predictions. This approach achieves SOTA on the 7th LSVOS Challenge (RVOS track). A practical solution with full repo under Apache💙

👉Review https://t.ly/aH4mB
👉Paper https://arxiv.org/pdf/2509.16972
👉Repo https://github.com/magic-research/Sa2VA

🏆MOSEv2 Challenge Winner🏆

👉A practical solution for complex segmentation based on the Segment Concept (SeC), a concept-driven segmentation framework that shifts from conventional feature matching to the progressive construction and utilization of high-level, object-centric representations. Repo under Apache 2.0💙

👉Review https://t.ly/2MjNm
👉Paper arxiv.org/pdf/2509.19183
👉Paper (SeC) arxiv.org/pdf/2507.15852
👉Repo github.com/OpenIXCLab/SeC
👉Project rookiexiong7.github.io/projects/SeC/

🌀 CLOPS: Vision-Driven Avatar 🌀

👉CLOPS is the first human avatar solely uses egocentric vision to perceive its surroundings and navigate. CLOPS is able to realistically move in a scene and use egocentric vision in order to find a goal in a loop of visual perception & motion. Code announced💙

👉Review https://t.ly/RXp64
👉Paper https://arxiv.org/pdf/2509.19259
👉Project markos-diomataris.github.io/projects/clops/
👉Repo TBA