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

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

#AI #chatGPT
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🌈 New SOTA Video Depth 🌈

πŸ‘‰DVD is the new Video Depth Estimation SOTA with full training suite available under Apache2.0πŸ’™

πŸ‘‰Review https://t.ly/gpCkG
πŸ‘‰Paper https://arxiv.org/pdf/2603.12250
πŸ‘‰Project https://dvd-project.github.io/
πŸ‘‰Repo github.com/EnVision-Research/DVD
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πŸ€–Physically-Plausible HumanπŸ€–

πŸ‘‰PhysMoDPO is a novel direct preference optimization framework for humanoid motion generation. Repo under MITπŸ’™

πŸ‘‰Review https://t.ly/clf8w
πŸ‘‰Paper https://arxiv.org/pdf/2603.13228
πŸ‘‰Project https://mael-zys.github.io/PhysMoDPO/
πŸ‘‰Repo https://github.com/Mael-zys/PhysMoDPO
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🍧10,000Γ— faster SAM-3D🍧

πŸ‘‰Fast SAM 3D Body achieves up to 10.9Γ— speedup, over 10,000Γ— faster MHR-to-SMPL conversion -> real-time humanoid control from RGB. Repo availableπŸ’™

πŸ‘‰Review https://t.ly/uHx84
πŸ‘‰Paper https://arxiv.org/pdf/2603.15603
πŸ‘‰Project yangtiming.github.io/Fast-SAM-3D-Body-Page/
πŸ‘‰Repo https://github.com/yangtiming/Fast-SAM-3D-Body
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πŸ“Material-Aware GroupingπŸ“

πŸ‘‰Material Magic Wand (Adobe) is a tool for material-aware grouping of parts in untextured 3D meshes. Given one selected part, it automatically retrieves the other parts in the same shape by its material. Repo announcedπŸ’™

πŸ‘‰Review https://t.ly/q00SU
πŸ‘‰Paper https://arxiv.org/pdf/2603.17370
πŸ‘‰Project umangi-jain.github.io/material-magic-wand/
πŸ‘‰Repo TBA
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πŸ¦ͺOccAny: Universal 3D OccupancyπŸ¦ͺ

πŸ‘‰OccAny by Valeo is a novel unified framework for generalized unconstrained urban 3D occupancy prediction. Repo under Apache 2.0πŸ’™

πŸ‘‰Review https://t.ly/FFiU0
πŸ‘‰Paper https://arxiv.org/pdf/2603.23502
πŸ‘‰Project https://valeoai.github.io/OccAny/
πŸ‘‰Repo https://github.com/valeoai/OccAny
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🐍Pose-Appearance-Motion for HOI🐍

πŸ‘‰PAM is a novel Pose–Appearance–Motion Engine for controllable Hand–Object Interaction SOTA video generation. Repo/models availableπŸ’™

πŸ‘‰Review https://t.ly/JU4MD
πŸ‘‰Paper arxiv.org/pdf/2603.22193
πŸ‘‰Project gasaiyu.github.io/PAM.github.io/
πŸ‘‰Repo https://github.com/GasaiYU/PAM
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πŸ’₯ GaussianGPT 3D GSCπŸ’₯

πŸ‘‰From TUM, GaussianGPT: transformer-based 3D Gaussians generation via next-token prediction -> full 3D complex indoor scene. Repo announcedπŸ’™

πŸ‘‰Review https://t.ly/bj-lL
πŸ‘‰Paper arxiv.org/pdf/2603.26661
πŸ‘‰Project nicolasvonluetzow.github.io/GaussianGPT/
πŸ‘‰Repo TBA
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πŸ‘ŒHandX: Scaling Hands MotionπŸ‘Œ

πŸ‘‰ HandX is a unified foundation spanning data, annotation, and evaluation: novel large-scale dataset of bimanual & dexterous motions with fine-grained textual. Around 6M frames. Repo availableπŸ’™

πŸ‘‰Review https://t.ly/1nGxw
πŸ‘‰Paper https://arxiv.org/pdf/2603.28766
πŸ‘‰Project https://handx-project.github.io/
πŸ‘‰Repo github.com/handx-project/HandX
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🌡SOTA Training-Free In-Context Segmentation🌡

πŸ‘‰INSID3 is the new SOTA, training-free approach that segments concepts at varying granularities only from frozen DINOv3 features, given an in-context example. Repo under Apache 2.0πŸ’™

πŸ‘‰Review https://t.ly/NVWHN
πŸ‘‰Paper arxiv.org/pdf/2603.28480
πŸ‘‰Project visinf.github.io/INSID3/
πŸ‘‰Repo github.com/visinf/INSID3
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πŸͺ¬Camera Raw Image GenerationπŸͺ¬

πŸ‘‰RawGen by #Samsung is a generative approach that learns the complex distribution of raw sensor data directly, enabling high-fidelity generation from either text descriptions or standard sRGB images across arbitrary camera sensors. Linear raw image once, then apply any ISP operation. Repo announcedπŸ’™

πŸ‘‰Review https://t.ly/_QVKP
πŸ‘‰Paper https://arxiv.org/pdf/2604.00093
πŸ‘‰Project https://dy112.github.io/rawgen-page/
πŸ‘‰Repo TBA
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If you have to invest TODAY 1B$ on a frontier tech for the next decade, would you invest in space, agentic, quantum or frugal GPUs? Vote here: https://t.ly/hSx6i
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🍎Video Object Deletion🍎

πŸ‘‰Void by Netflix is a novel video object removal framework designed to perform physically-plausible inpainting in very complex scenarios. Repo under Apache 2.0πŸ’™

πŸ‘‰Review https://t.ly/cMVny
πŸ‘‰Paper https://arxiv.org/pdf/2604.02296
πŸ‘‰Project https://void-model.github.io/
πŸ‘‰Repo https://github.com/Netflix/void-model
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πŸ”₯Vanast: VTON w/ Human AnimationπŸ”₯

πŸ‘‰SNU unveils a novel unified framework that generates garment-transferred human animation videos directly from a single human/garment images, and pose guidance clip. Repo announcedπŸ’™

πŸ‘‰Review https://t.ly/c0t79
πŸ‘‰Paper arxiv.org/pdf/2604.04934
πŸ‘‰Project hyunsoocha.github.io/vanast/
πŸ‘‰Repo github.com/snuvclab/vanast
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πŸ”₯BoxerNet: SOTA 2D->3D BBsπŸ”₯

πŸ‘‰Boxer by META: transformer-based network to lift 2D BB proposals into 3D, followed by multi-view fusion and geometric filtering to produce globally consistent de-duplicated 3DBBs in metric world space. Repo under A-NC 4.0 InternationalπŸ’™

πŸ‘‰Review https://t.ly/mlmV1
πŸ‘‰Paper https://arxiv.org/pdf/2604.05212
πŸ‘‰Project facebookresearch.github.io/boxer/
πŸ‘‰Repo github.com/facebookresearch/boxer
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Hinton our guest in Pavia (remotely) πŸ’šπŸ˜ˆ

Would you see a clip about the interview?
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Here the preview, tomorrow the full clip from official source :)
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πŸͺž1.1M Metric VTON DatasetπŸͺž

πŸ‘‰Google's Fit-Inclusive Try-on: large-scale VTO dataset comprising over 1.13M try-on image triplets accompanied by precise body and garment measurements. Repo & dataset announcedπŸ’™

πŸ‘‰Review https://t.ly/cs-pt
πŸ‘‰Paper arxiv.org/pdf/2604.08526
πŸ‘‰Project johannakarras.github.io/FIT/
πŸ‘‰Repo TBA
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🐞6D Object Pose w/ Deformation🐞

πŸ‘‰DeSOPE by Xidian & #MagicLeap is a novel large-scale dataset for 6DoF deformed objects: 665K pose annotations produced via a semiautomatic pipeline. Repo & Dataset announcedπŸ’™

πŸ‘‰Review https://t.ly/M5VgX
πŸ‘‰Paper https://arxiv.org/pdf/2604.06720
πŸ‘‰Project https://desope-6d.github.io/
πŸ‘‰Repo TBA
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πŸ”₯SOTA 3D Detection in the wildπŸ”₯

πŸ‘‰WildDet3D is a novel unified geometry-aware architecture for 3D detection that natively accepts text, point, and box prompts and can incorporate auxiliary depth signals at inference time. New SOTA! Repo, models and iphone πŸ’™

πŸ‘‰Review https://t.ly/8NxBN
πŸ‘‰Paper arxiv.org/pdf/2604.08626
πŸ‘‰Project allenai.github.io/WildDet3D/
πŸ‘‰Repo github.com/allenai/WildDet3D
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