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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🪙MOMENTUM #NeurIPS 2025 🪙

👉MOMENTUM by Google (H/T Huguens Jean, Ph.D.) is a production multimodal agent architecture built on the Google ADK. It orchestrates 22 specialized tools (Gemini for reasoning, Imagen 4.0 for image generation, and Veo 3.1 for synthesis). Code announced💙

👉Review https://t.ly/06h7Q
👉Paper https://momentum-project-page-232993426383.us-central1.run.app/momentum_paper.pdf
👉Project https://momentum-project-page-232993426383.us-central1.run.app/
👉Repo TBA
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😶‍🌫️ SOTA Full-Head Synthesis 😶‍🌫️

👉HyPlaneHead, the new SOTA in full-head image synthesis, delivering HQ results with significantly fewer artifacts compared to existing 3D-aware models. Repo announced💙

👉Review https://t.ly/WYfP3
👉Paper arxiv.org/pdf/2509.16748
👉Project https://lhyfst.github.io/hyplanehead/
👉Repo github.com/lhyfst/HyPlaneHead
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🍟 AnyTouch 2 is out 🍟

👉AnyTouch 2 is a general tactile representation learning framework for diverse optical tactile sensors that unifies object-level understanding with fine-grained, force-aware dynamic perception. Repo, Model & Data💙

👉Review https://t.ly/fP4dP
👉Paper https://arxiv.org/pdf/2602.09617
👉Project gewu-lab.github.io/AnyTouch2/
👉Repo github.com/GeWu-Lab/AnyTouch2
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🍌 AGENT BANANA (SOTA) 🍌

👉Agent Banana is the novel SOTA agentic system for HD, native-resolution image editing through reasoning-based NL interaction, where each edit is context-aware, logically dependent, and locally precise. Code announced💙

👉Review https://t.ly/EXaCH
👉Paper https://arxiv.org/pdf/2602.09084
👉Project https://agent-banana.github.io/
👉Repo https://github.com/taco-group/agent-banana
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🛠️ IndustryShapes 6D Pose 🛠️

👉IndustryShapes by NTUA is a new RGB-D dataset of industrial tools, designed for both instance-level and novel object 6D pose estimation. Dataset available💙

👉Review https://t.ly/KKcuH
👉Paper https://arxiv.org/pdf/2602.05555
👉Project https://pose-lab.github.io/IndustryShapes/
👉Dataset https://huggingface.co/datasets/POSE-Lab/IndustryShapes
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🤖Generalized Human Tracking🤖

👉Beijing Institute of Technology & Humanoid Robotics Shangai present a novel learning framework for general humanoid whole-body control. Impressive results in imitation.

👉Review https://t.ly/ucmuB
👉Paper arxiv.org/pdf/2601.23080
👉Project zeonsunlightyu.github.io/RGMT.github.io
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🫧SurfPhase: 3D Interfacial Dynamics🫧

👉SurfPhase is a novel model for reconstructing 3D interfacial dynamics from sparse camera views. Repo/Dataset announced💙

👉Review https://t.ly/g2P5F
👉Paper https://arxiv.org/pdf/2602.11154
👉Project https://yuegao.me/SurfPhase/
👉Repo github.com/yuegao/SurfPhase
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🪿Teaching AI to illusions🪿

👉Stroke of Surprise by NYCU is a novel generative framework that optimizes vector strokes to satisfy distinct semantic interpretations at different drawing stages. As strokes are progressively added, the sketch reveals a completely different subject. Code released💙

👉Review https://t.ly/98Oim
👉Paper https://lnkd.in/dTA7iuce
👉Project https://lnkd.in/dhTMGw23
👉Repo https://lnkd.in/deQyDGFu
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🥝Conversational Segmentation🥝

👉CIS grounds abstract, intent-oriented concepts into pixel-accurate masks, reasoning about affordances, physics, and functional properties. Code/Demo released💙

👉Review https://t.ly/SsG57
👉Paper arxiv.org/pdf/2602.13195
👉Project glab-caltech.github.io/converseg/
👉Repo github.com/AadSah/ConverSeg
👉Demo glab-caltech.github.io/converseg/#interactive-demo
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📲 Efficient VLMs 📲

👉CoPE-VideoLM is a codec-aware tokenization framework for VLM to replace dense RGB encoding w/ light structured representations derived from codec primitives. Token -93% / time-to-first-token -86%! Code announced💙

👉Review https://t.ly/3_GqN
👉Paper https://arxiv.org/pdf/2602.13191
👉Project https://sayands.github.io/cope/
👉Repo TBA
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🐙Dex4D: Task-Agnostic Track🐙

👉Dex4D by CMU is a novel approach for unseen objects and poses, scene layouts, backgrounds, & task trajectories. Code under Apache 2.0💙

👉Review https://t.ly/ZGx9T
👉Paper arxiv.org/pdf/2602.15828
👉Project dex4d.github.io/
👉Sim github.com/Dex4D/Dex4D-Simulation
👉Vision github.com/Dex4D/Dex4D-Vision
👉HW https://github.com/Dex4D/Dex4D-Hardware
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🚤Video Neural Compression🚤

👉TeCoNeRV: adapting INR hypernetworks to compress videos efficiently at higher resolutions. Impressive: +5.35dB PSNR, -36% bitrates & 1.5-3× faster. Code announced💙

👉Review https://t.ly/0AtCK
👉Paper arxiv.org/pdf/2602.16711
👉Project namithap10.github.io/teconerv/
👉Repo github.com/namithap10/TeCoNeRV/
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🔥New SOTA Planar Tracking🔥

👉WOFTSAM by the Visual Recognition Group (CTU) is a novel planar tracker that combine robust long-term segmentation by SAM2 with 8 degrees-of-freedom homography pose estimation. Repo under BY-NC-SA 4.0💙

👉Review https://t.ly/VUOe5
👉Paper https://lnkd.in/dZfc_DhQ
👉Repo https://lnkd.in/dAcneJGn
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🫸 World-Grounded Hand-Obj🫸

👉WHOLE jointly reconstructs coherent hand and object motion in the world space by guiding a generative motion prior. Code announced💙

👉Review https://t.ly/c5w8h
👉Paper https://arxiv.org/pdf/2602.22209
👉Project https://judyye.github.io/whole-www/
👉Repo TBA
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🧱Solaris: generative #Minecraft🧱

👉NYU unveils Solaris, multiplayer video world model in Minecraft, which generates consistent first-person observations for two players simultaneously. Impressive work. Repo & Dataset💙

👉Review https://t.ly/VrcrT
👉Paper https://arxiv.org/pdf/2602.22208
👉Project https://solaris-wm.github.io/
👉Repo https://github.com/solaris-wm/
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