🦑Unified Segmentation n' Retrieval🦑

👉FoundYou gets an example of your object and it segments the same physical instance in a new image or retrieve it from a large gallery with ONE super-compact model. Repo/demo available💙

👉Review https://lnkd.in/p/ex2qnKHW
👉Paper arxiv.org/pdf/2608.29917
👉Project https://lnkd.in/eNEUB_nV
👉Repo https://lnkd.in/eRyDY6Ue

🍚Vision Weight Estimation🍚

👉Doppio is a novel video dataset capturing video of falling ground coffee, paired with precise, per-frame ground-truth weight measurements: OCR readings are extracted from the display, smoothed and time-lag compensated, and paired with per-frame weight annotations. Repo to be released under Apache💙

👉Review https://www.linkedin.com/posts/visionarynet_computer-vision-weight-estimation-activity-7501900695457951744-ArBO
👉Paper https://lnkd.in/eHuy87SX
👉Project https://lnkd.in/e9g9zeK3
👉Repo https://lnkd.in/emUePTiq

🪣Weather-Conditioned Depth Anything🪣

👉Weather-Conditioned Depth Anything from Texas A&M is the new SOTA in weather-robust depth estimation. A curated mix of real and synthetic degradation datasets to extract content-independent, degradation-aware weather embeddings. Repo under Apache💙

👉Review https://lnkd.in/p/eW-dsepD
👉Paper https://lnkd.in/er_MvVft
👉Project https://lnkd.in/ehXPs3C7
👉Repo https://lnkd.in/edk7Ts_r

+++ Mistral raises 3B € +++

👉Discussion: https://lnkd.in/p/eVpF--VW

👻Emerging Objs from Motion👻

👉Motion boundaries provide a strong signal for object-level grouping and can be used to derive pseudo-instance supervision. Suitable for: mono-depth, 3D object detection, 3D occupancy, and end-to-end planning. Repo under Apache 2.0💙

👉Review https://lnkd.in/p/eezZrSJE
👉Paper https://arxiv.org/pdf/2609.04348
👉Project https://tj12342.github.io/object-concepts-from-motion/
👉Repo https://github.com/TJ12342/object-concepts-from-motion/tree/main

🔥#AIwithPapers: we are 17,000+🔥

👉 Even though 100+ bots are trying to join the discussion chats every day, there are 17,000 of us! Almost all of us are still humans 🧟

😈 Invite -> https://xn--r1a.website/AI_DeepLearning

🏀McByte++ tracking-by-detection🏀

👉McByte++ is the newer extension of McByte that advances training-free sports MOT toward long-term ID tracking, while simultaneously improving efficiency and runtime performance. Repo under Apache 2.0💙

👉Review https://lnkd.in/p/e4-diVJS
👉Paper https://lnkd.in/e_Vxky-b
👉Repo https://lnkd.in/e8SeCYmk

🔥🔥 Marigold V2 is out 🔥🔥

👉Marigold V2 is out: depth, (impressive) see-through depth, surface normals, albedo, and other dense modalities. SOTA results. Repo under Apache 2.0💙

#AI #deeplearning #AIwithPapers

👉Review https://lnkd.in/p/eKM44yDQ
👉Paper https://arxiv.org/pdf/2609.08084
👉Repo https://github.com/huawei-bayerlab/marigold-v2
👉Project https://huggingface.co/spaces/huawei-bayerlab/marigold-v2-web

🦺Efficient/Scalable Video Pretraining🦺

👉LeVJEPA1 (Yann Lecun) is the first video encoder trained under LeJEPA’s collapse-free objective, and evaluate it under frozen probing against video and image pretraining baselines retrained on identical data, in both epoch-matched and FLOP-matched regimes. Repo under MIT💙

👉Review https://lnkd.in/p/eJQAm3AN
👉Paper https://lnkd.in/eCzzTiNH
👉Project https://levjepa.github.io/
👉Repo https://lnkd.in/etiF5CDj

🔥 RelateAnything is gold! 🔥

👉RelateAnything is a 53M-parameter relation model that takes an image and a set of regions from any source and returns scored relations over a predicate vocabulary supplied at inference as a list of strings. Impressive results. Repo under Apache 2.0💙

👉Review https://lnkd.in/p/etAcdFM3
👉Paper https://arxiv.org/pdf/2609.12552
👉Repo https://github.com/Maelic/RelateAnything
👉Project https://maelic.github.io/RelateAnythingProject/

👋 EventEgoHands++ is out! 👋

👉EventEgoHands++ is a novel framework for event-based 3D hand mesh reconstruction from an egocentric viewpoint. 1M+ samples dataset! Code/Data released💙

👉Review https://lnkd.in/p/eTbPvXbW
👉Paper https://arxiv.org/pdf/2609.17189
👉Repo https://github.com/ryhara/EventEgoHandsV2
👉Project https://ryhara.github.io/EventEgoHandsV2/

💦SOTA Splashing Liquids💦

👉SplashSplat reconstructs splashing liquids from real multi-view vide. Impose physical structure only where the observations can constrain it. Impressive results, SOTA. Code TBR under MIT💙

👉Review https://lnkd.in/p/ejMTHcp7
👉Paper https://arxiv.org/pdf/2609.20818
👉Project niko-creater.github.io/splashsplat-web/
👉Repo https://github.com/Niko-creater/Splashsplat

+++ Breaking +++

🔥Agentic Image-to-Scene🔥

👉HARMONY by UPenn is a hierarchical chain-of-thought framework that leverages both agentic reasoning and visual geometry foundation. Impressive 3D scenes. Repo TBA💙

👉Review https://lnkd.in/p/ep2hmRSp
👉Paper https://arxiv.org/pdf/2609.26793
👉Project https://cwchenwang.github.io/harmony/
👉Data https://huggingface.co/datasets/ShufanSun/harmony

🍿PanoSeg3R: SOTA 3D Segmentation🍿

👉PanoSeg3R is a novel feed-forward framework for 3D panoramic semantic segmentation. New SOTA. Code coming💙

👉Review https://lnkd.in/p/eKCKWv3g
👉Paper https://arxiv.org/pdf/2609.22687
👉Project https://harryyoon777.github.io/PanoSeg3R/#
👉Repo TBA

🩻Universal X-ray Segmentation🩻

👉FleXray: universal anatomical segmentation across the entire body in clinical X-rays. Built on a scalable, physics-based generative X-ray data engine. Repo under MIT💙

👉Review https://lnkd.in/p/e9MUk_eq
👉Paper https://arxiv.org/pdf/2609.26756
👉Project https://flexray.csail.mit.edu/
👉Repo https://github.com/VictorButoi/FleXray

🦴3D Foundational Radiology🦴

👉nnFoundation: 3D radiological foundation models designed for transferable representation learning across heterogeneous tasks/datasets. Models released💙

👉Review https://lnkd.in/p/eNajRGBi
👉Paper https://arxiv.org/pdf/2609.26924
👉Models https://huggingface.co/collections/MIC-DKFZ/nnfoundation

🔥TrackEverything is out🔥

👉TrackEverything is the first 3D point tracker capable of tracking all visible points across long horizons (1000+ frames). Repo announced💙

👉Review https://lnkd.in/p/eCPJ6h2B
👉Paper https://arxiv.org/pdf/2609.30222
👉Project https://trackeverything.github.io/
👉Repo https://github.com/ayushjain1144/trackeverything

🔥Ego-Exo4D Human Dataset🔥

👉Form the University of Austin, Ego-Exo4D-HM: large-scale dataset of 4D human motion reconstructions for Ego-Exo4D’s captures + reconstruction pipeline. Code, dataset, and docs 💙

👉Review https://lnkd.in/p/eVFt9jPr
👉Paper https://lnkd.in/eWj4cD7T
👉Project https://lnkd.in/euPqVNxV

🔥🔥 70,000+ 🔥🔥

👉 Crazy how a boring science project (no kittens, no rants, no personal dramas) can reach for 70,000+ followers. Speechless.

Love u 💛

👉 https://lnkd.in/p/eD6Xxdxi