AI with Papers - Artificial Intelligence & Deep Learning
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All the AI with papers. Every day fresh updates about #DeepLearning, #MachineLearning, LLMs and #ComputerVision

Curated by Alessandro Ferrari | https://www.linkedin.com/in/visionarynet/

#artificialintelligence #machinelearning #ml #AI
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✂️ VideoCutLER: Simple UVIS ✂️

👉VideoCutLER is a simple unsupervised video instance segmentation (UVIS) method without relying on optical flows

😎Review https://t.ly/PBBjG
😎Paper arxiv.org/pdf/2308.14710.pdf
😎Project people.eecs.berkeley.edu/~xdwang/projects/CutLER
😎Code github.com/facebookresearch/CutLER/tree/main/videocutler
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🐦 3D Pigeons Pose & Tracking 🐦

👉 3D-MuPPET: estimate and track 3D poses of pigeons with multiple-views

😎Review https://t.ly/jfAJJ
😎Paper arxiv.org/pdf/2308.15316.pdf
😎Code github.com/alexhang212/3D-MuPPET/
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🎍RoboTAP: Dense Tracking for Few-Shot Imitation🎍

👉RoboTAP: novel dense tracking representation for robotic arm

😎Review https://t.ly/MCO_V
😎Paper arxiv.org/pdf/2308.15975.pdf
😎Project https://robotap.github.io/
😎Code github.com/deepmind/tapnet
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FACET: Fairness in Computer Vision

👉#META AI opens a large, publicly available dataset for classification, detection & segmentation. Potential performance disparities & challenges across sensitive demographic attributes

😎Review https://t.ly/mKn-t
😎Paper arxiv.org/pdf/2309.00035.pdf
😎Dataset https://facet.iss.onetademolab.com/
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♊️ Doppelgangers in Structures ♊️

👉A novel learning-based approach for visual disambiguation: distinguishing illusory matches to produce correct, disambiguated #3D reconstructions

😎Review https://t.ly/9yLot
😎Paper arxiv.org/pdf/2309.02420.pdf
😎Code github.com/RuojinCai/Doppelgangers
😎Project doppelgangers-3d.github.io/
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🍃 Tracking Anything with Decoupled VOS 🍃

👉A novel VOS approach that extends SAM for open-world video segmentation with no user input required

😎Review https://t.ly/xeobR
😎Paper arxiv.org/pdf/2309.03903.pdf
😎Project hkchengrex.com/Tracking-Anything-with-DEVA
😎Code github.com/hkchengrex/Tracking-Anything-with-DEVA
😎Colab https://colab.research.google.com/drive/1OsyNVoV_7ETD1zIE8UWxL3NXxu12m_YZ
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🪷 Diffusive Consistent Video Editing 🪷

👉 Weizmann Institute of Science unveils TokenFlow, a novel text-to-image diffusion model for text-driven video editing

😎Review https://t.ly/ru8km
😎Paper arxiv.org/pdf/2307.10373.pdf
😎Project diffusion-tokenflow.github.io
😎Code github.com/omerbt/TokenFlow
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🔥🔥 #META's DINOv2 is now commercial! 🔥🔥

👉Universal features for image classification, instance retrieval, video understanding, depth & semantic segmentation. Now suitable for commercial.

😎Review https://t.ly/LNrGy
😎Paper arxiv.org/pdf/2304.07193.pdf
😎Code github.com/facebookresearch/dinov2
😎Demo dinov2.metademolab.com/
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🧄FreeMan: towards #3D Humans 🧄

👉FreeMan: the first large-scale, real-world, multi-view dataset for #3D human pose estimation. 11M frames!

😎Review https://t.ly/ICxpA
😎Paper arxiv.org/pdf/2309.05073.pdf
😎Project wangjiongw.github.io/freeman
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🦊 MagiCapture: HD Multi-Concept Portrait 🦊

👉KAIST unveils MagiCapture: integrating subject and style concepts to generate high-resolution portrait images using just a few subject and style references

😎Review https://t.ly/c9rOo
😎Paper https://arxiv.org/pdf/2309.06895.pdf
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Dynamic NeRFs for Soccer

👉SoccerNeRF: first attempt of "cheap" NeRF applied to football for reconstructing soccer replays in space and time.

😎Review https://t.ly/Ywcvk
😎Paper arxiv.org/pdf/2309.06802.pdf
😎Project https://soccernerfs.isach.be/
😎Code github.com/iSach/SoccerNeRFs
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☢️ GlueStick: Graph Neural Matching ☢️

👉GlueStick is joint deep matcher for points and lines that leverages the connectivity information between nodes to better glue them together

😎Review https://t.ly/Atxqo
😎Paper arxiv.org/pdf/2304.02008.pdf
😎Code https://github.com/cvg/GlueStick
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🫀CPR-Coach: Neural Cardiopulmonary Resuscitation🫀

👉CPR-Coach: fine-grained action recognition in cardiopulmonary resuscitation

😎Review https://t.ly/Qbg4K
😎Paper arxiv.org/pdf/2309.11718.pdf
😎Code github.com/Shunli-Wang/CPR-Coach
😎Project shunli-wang.github.io/CPR-Coach
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🧪 NeuralLabeling with NeRF 🧪

👉Annotating a scene by generating segmentation masks, affordance maps, 2D bounding boxes, 3D BB, 6DOF poses, depth & meshes.

😎Review https://t.ly/1GPsj
😎Paper arxiv.org/pdf/2309.11966.pdf
😎Code github.com/FlorisE/neural-labeling
😎Project florise.github.io/neural_labeling_web
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🍟 DE-ViT: detecting everything via DINOv2 🍟

👉DE-ViT: open-set object detector based on DINOv2 backbone. It's the new SOTA on COCO & LVIS dataset

😎Review https://t.ly/_DAmt
😎Paper arxiv.org/pdf/2309.12969.pdf
😎Code https://github.com/mlzxy/devit
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🛵CoTracker: fast transformer-tracker🛵

👉META's CoTracker is a fast transformer-based model that can track any point in a video

😎Review https://t.ly/M36A_
😎Paper arxiv.org/pdf/2307.07635.pdf
😎Project https://co-tracker.github.io/
😎Code github.com/facebookresearch/co-tracker
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🌬️ Neural Blowing in Still Photos 🌬️

👉 A novel approach to animate human hair (and clothes) in a still portraits

😎Review https://t.ly/HKG0t
😎Paper arxiv.org/pdf/2309.14207.pdf
😎Project nevergiveu.github.io/AutomaticHairBlowing
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🌮 OW Indoor Segmentation 🌮

👉3D-OWIS is a novel open-world 3D indoor instance segmentation method (with auto-labeling scheme) to separate known/unknown category labels

😎Review https://t.ly/-7ALf
😎Paper arxiv.org/pdf/2309.14338.pdf
😎Code github.com/aminebdj/3D-OWIS
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🧱 Generating Scenes from Touch 🧱

👉#AI for synthesizing images from tactile signals (and vice versa) and apply it to a number of visuo-tactile synthesis tasks

😎Review https://t.ly/Gxr0L
😎Paper https://arxiv.org/pdf/2309.15117.pdf
😎Project https://fredfyyang.github.io/vision-from-touch
😎Code https://github.com/fredfyyang/vision-from-touch
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Decaf: 3D Face-Hand Interactions

👉The first learning-based MoCap to track human hands interacting with human faces in #3D from single monocular RGB videos

😎Review https://t.ly/070Tj
😎Paper arxiv.org/pdf/2309.16670.pdf
😎Project vcai.mpi-inf.mpg.de/projects/Decaf
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🌱 Making LLaMA See and Draw 🌱

👉Tencent #AI planted a SEED of Vision in Large Language Model. Making LLaMA see 'n' draw stuff.

😎Review https://t.ly/QiCAv
😎Paper arxiv.org/pdf/2310.01218.pdf
😎Code github.com/AILab-CVC/SEED
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