AI with Papers - Artificial Intelligence & Deep Learning – Telegram
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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✌️SOTA Generative SLP✌️

👉Stable Signer is a new sign language generative model. It redefines the SLP task as a hierarchical generation end-to-end task that only includes text understanding (Prompt2Gloss, Text2Gloss) and Pose2Vid. Repo with data 💙

👉Review https://t.ly/yKZhn
👉Paper arxiv.org/pdf/2512.04048
👉Project stablesigner.github.io/
👉Data github.com/SignLLM/Prompt2Sign/tree/main/tools-new-2025
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🐘TTSC for 3D Generative🐘

👉SpaceControl is the new SOTA training-free test-time method for explicit spatial control of 3D generation. Repo announced💙

👉Review https://t.ly/1zrah
👉Paper https://lnkd.in/dEWh3vep
👉Project https://lnkd.in/dScftUmm
👉Repo TBA
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🎷Layered PSD Diffusion🎷

👉OmniPSD produces layered PSD files with transparent alpha channels, separating text, foreground elements, and background into clean RGBA layers that can be directly edited in tools. Online Demo💙

👉Review https://t.ly/YNRAC
👉Paper arxiv.org/pdf/2512.09247
👉Project showlab.github.io/OmniPSD/
👉Demo https://www.lovart.ai/it
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🧱Pixel Art Volumetric Rendering🧱

👉Voxify3D is a novel differentiable two-stage framework bridging 3D mesh optimization with 2D pixel art supervision. Repo announced💙

👉Review https://t.ly/qPyNl
👉Paper https://lnkd.in/du5ikJGN
👉Project https://lnkd.in/dpiAjj5m
👉Repo TBA
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🫎 MoCapAnything is out 🫎

👉MoCapAnything is novel a reference-guided, factorized framework that first predicts 3D joint trajectories and then recovers asset-specific rotations via constraint-aware IK fitting. No code announced 🥲

👉Review https://t.ly/_Tw6t
👉Paper arxiv.org/pdf/2512.10881
👉Project animotionlab.github.io/MoCapAnything
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💚 MatAnyone 2 is out! 💚

👉MatAnyone 2 is the most advanced human video matting framework that preserves fine details by avoiding segmentation-like boundaries, while also shows enhanced robustness under challenging real-world conditions. Repo & Dataset announced💙

👉Review https://t.ly/vxOBO
👉Paper arxiv.org/pdf/2512.11782
👉Project pq-yang.github.io/projects/MatAnyone2
👉Repo github.com/pq-yang/MatAnyone2
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💷 SOTA Zero-Shot Stereo Matching💷

👉Fast-FoundationStereo by #Nvidia is a novel family of architectures that achieve, for the first time, strong zero-shot generalization at real-time frame rate via divide-&-conquer acceleration. Code & Data announced💙

👉Review https://t.ly/XD6pO
👉Paper https://lnkd.in/d9_YKW2A
👉Project https://lnkd.in/dKDxm7EX
👉Repo https://lnkd.in/dR4-PdsW
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👀DriverGaze360: Driver SOTA👀

👉DriverGaze360 is a large-scale 360◦ field of view driver attention dataset, containing ∼1M gaze-labeled frames. Code & Dataset announced💙

👉Review https://t.ly/ZcoUw
👉Paper arxiv.org/pdf/2512.14266
👉Project av.dfki.de/drivergaze360/
👉Repo github.com/dfki-av/drivergaze360
👉Data av.dfki.de/drivergaze360/dataset
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🫠FlexAvatar: 3D Heads🫠

👉TUM introduces FlexAvatar, a novel method for creating HQ and complete 3D head avatars from a single image. Code announced💙

👉Review https://t.ly/Rkdtd
👉Paper arxiv.org/pdf/2512.15599
👉Project tobias-kirschstein.github.io/flexavatar/
👉Repo TBA
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🏜️ Depth Any Panoramas 🏜️

👉DAP is the new SOTA foundation model for panoramic depth estimation with a large scale dataset. Data & Repo under MIT💙

👉Review https://t.ly/LaUmd
👉Paper arxiv.org/pdf/2512.16913
👉Project https://lnkd.in/dvqNV9jx
👉Repo https://lnkd.in/dmNzhb-7
👉Demo https://lnkd.in/dDwjMF3u
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🎯Generative Refocusing is out🎯

👉Generative Refocusing is a two-step process that uses DeblurNet to recover all-in-focus images from various inputs and BokehNet for creating controllable bokeh (in semi-supervised mode). Repo under Apache2.0💙

👉Review https://t.ly/8t7PA
👉Paper arxiv.org/pdf/2512.16923
👉Project generative-refocusing.github.io/
👉Repo github.com/rayray9999/Genfocus
👉Demo huggingface.co/spaces/nycu-cplab/Genfocus-Demo
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TOP 5 Papers you loved in 2025

👉 In 2025 novel architectures have redefined efficiency and accuracy, and almost every day brought a new SOTA in image understanding, tracking, and GenAI. It’s been an inspiring ride, and 2026 it will be even wilder. This community (LinkedIn + Telegram) is now around 80,000+ people.

𝐏𝐚𝐩𝐞𝐫𝐬 (𝐛𝐲 𝐲𝐨𝐮𝐫 𝐩𝐫𝐞𝐟𝐞𝐫𝐞𝐧𝐜𝐞):
3D LLM https://t.ly/ejr1s
DynOMo https://t.ly/t5pCf
Track Transf. https://t.ly/NPyW4
YOLOv12 https://t.ly/jj1oR
G-Surface Tracking https://t.ly/udpMq

Thank you all💙
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🦙 Depth as Neural Implicit 🦙

👉InfiniDepth represents depth as neural implicit fields, "infinite" (i.e.16K) resolution and geometrical details. Repo under Apache 2.0💙

👉Review https://t.ly/4we5t
👉Paper https://lnkd.in/dpiHQExj
👉Project https://lnkd.in/dy3JxKye
👉Repo https://lnkd.in/dAXbnK5z
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🔥 Back from Holidays mood 🔥
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🌍Label Any Object in 3D 🌍

👉LabelAny3D: novel analysis-by-synthesis framework that reconstructs holistic 3D scenes from 2D to efficiently produce HQ 3D BBs annotations. Repo under CC-BY-4.0 license💙

👉Review https://t.ly/bO93j
👉Paper https://lnkd.in/dYb97zWG
👉Project https://lnkd.in/dJ9UKERb
👉Repo https://lnkd.in/d9SxtmiA
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🔥 New #AI Startups in 2026? 🔥

In 2026, which area would you focus on?
🤖Agents → workflows, copilots, etc.
🏭Vertical AI → Pharma, Automotive, Energy ...
🧠Infrastructure → MLOps, Security, Cost Control ...
🎨AI for Creators/Media → Video, avatars, contents ...

Please, help me understanding what's next with this poll on LinkedIn :)

https://www.linkedin.com/posts/visionarynet_ai-ai-deeplearning-activity-7415377341779996672-sQO1

LUV U \m/
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