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AI with Papers - Artificial Intelligence & Deep Learning

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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📈 Telegram 频道 AI with Papers - Artificial Intelligence & Deep Learning 的分析概览

频道 AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 17 261 名订阅者,在 技术与应用 类别中位列第 7 497,并在 马来西亚 地区排名第 2 130 位。

📊 受众指标与增长动态

自 невідомо 创建以来,项目保持高速增长,吸引了 17 261 名订阅者。

根据 22 十月, 2026 的最新数据,频道保持稳定运转。过去 30 天订阅人数变化为 253,过去 24 小时变化为 -1,整体触达仍然可观。

  • 认证状态: 未认证
  • 互动率 (ER): 平均受众互动率为 18.98%。内容发布后 24 小时内通常能获得 7.07% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 3 275 次浏览,首日通常累积 1 220 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 23。
  • 主题关注点: 内容集中在 framework, object, dataset, tba, depth 等核心主题上。

📝 描述与内容策略

作者将该频道定位为表达主观观点的平台:
“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”

凭借高频更新(最新数据采集于 23 十月, 2026),频道始终保持新鲜度与高覆盖。分析显示受众积极互动,使其成为 技术与应用 类别中的关键影响点。

17 261
订阅者
-124 小时
+67 天
+25330 天
帖子存档
🍧10,000× faster SAM-3D🍧 👉Fast SAM 3D Body achieves up to 10.9× speedup, over 10,000× faster MHR-to-SMPL conversion -> real-time humanoid control from RGB. Repo available💙 👉Review https://t.ly/uHx84 👉Paper https://arxiv.org/pdf/2603.15603 👉Project yangtiming.github.io/Fast-SAM-3D-Body-Page/ 👉Repo https://github.com/yangtiming/Fast-SAM-3D-Body

🤖Physically-Plausible Human🤖 👉PhysMoDPO is a novel direct preference optimization framework for humanoid motion generation. Repo under MIT💙 👉Review https://t.ly/clf8w 👉Paper https://arxiv.org/pdf/2603.13228 👉Project https://mael-zys.github.io/PhysMoDPO/ 👉Repo https://github.com/Mael-zys/PhysMoDPO

🌈 New SOTA Video Depth 🌈 👉DVD is the new Video Depth Estimation SOTA with full training suite available under Apache2.0💙 👉Review https://t.ly/gpCkG 👉Paper https://arxiv.org/pdf/2603.12250 👉Project https://dvd-project.github.io/ 👉Repo github.com/EnVision-Research/DVD

☄️OmniStream: Perceive-Reconstruct-Act ☄️ 👉Novel unified streaming visual backbone that effectively perceives, reconstructs, and acts from diverse visual inputs. Repo/Models announced💙 👉Review https://t.ly/_zZMO 👉Paper arxiv.org/pdf/2603.12265 👉Project go2heart.github.io/omnistream/ 👉Repo github.com/Go2Heart/OmniStream

🍓Surface Light Tokenizer🍓 👉Apple unveils LITO a novel latent flow matching model enables HQ image-to-3D. Latent representation that encodes a surface light field into a compact set of latent vectors. Impressive results but no code🥲 👉Review https://t.ly/xcWNe 👉Paper https://lnkd.in/dYHwY4YX 👉Project https://lnkd.in/dtJT8bXy

🔥Holistic 3D Spatial Intelligence🔥 👉Holi-Spatial is the first fully automated pipeline capable of converting raw video streams into holistic 3D spatial annotations without human intervention. Code/Data announced💙 👉Review https://t.ly/PDpr9 👉Paper https://lnkd.in/dTbMuZCm 👉Project https://lnkd.in/d66CYB4q 👉Repo https://lnkd.in/dAGzShXj

📊Real-Time Scene Graph📊 👉REACT++ by Umea University is the new state-of-the-art model for real-time SGG: 20% faster with a gain of 10% in relation prediction accuracy on average. Code under MIT💙 👉Review https://t.ly/c12VX 👉Paper https://arxiv.org/pdf/2603.06386 👉Repo https://github.com/Maelic/SGG-Benchmark

🎪SOTA Arbitrary Tracking🎪 👉TAPFormer is the novel SOTA transformer-based framework that performs asynchronous temporal-consistent fusion of frames and events for robust and high-freq point tracking. Repo & Dataset under MIT💙 👉Review https://t.ly/-q4wm 👉Paper https://arxiv.org/pdf/2603.04989 👉Project http://tapformer.github.io/ 👉Repo https://github.com/ljx1002/TAPFormer

🍧Monocular 3D Clothed Human🍧 👉MultiGO++ is a novel framework for monocular 3D clothed human reconstruction via geometry-texture collaboration. New SOTA but no code announced🥲 👉Review https://t.ly/YKY44 👉Paper arxiv.org/pdf/2603.04993 👉Project 3dagentworld.github.io/multigo++

Could be useful for you seeing a few (verified) job posting about AI in this channel?
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🍙Any Resolution, Any Geometry🍙 👉Ultra Resolution Geometry Transformer (URGT) for arbitrary resolutions (e.g. 4K, 6K, 8K) depth–normal estimation. New SOTA. Repo under MIT💙 👉Review https://t.ly/HXg1n 👉Paper arxiv.org/pdf/2603.03026 👉Project dreamaker-mrc.github.io/Any-Resolution-Any-Geometry/ 👉Repo github.com/Dreamaker-MrC/Any-Resolution-Any-Geometry

🐪DuoMo: Dual Motion Diffusion🐪 👉DuoMo by #Meta is a novel generative method that recovers human motion in world-space coordinates from unconstrained videos with noisy or incomplete observations. Code announced💙 👉Review https://t.ly/dnA3K 👉Paper arxiv.org/pdf/2603.03265 👉Project yufu-wang.github.io/duomo/ 👉Repo TBA

🪿All Point Clouds-One Encoder🪿 👉Utonia is a step toward one-from-all and one-for-all point cloud encoder. It pretrains a single encoder on diverse point cloud data and reuses it as a reliable backbone for downstream tasks. Code under Apache 2.0💙 👉Review https://t.ly/yqSyZ 👉Paper https://arxiv.org/pdf/2603.03283 👉Project https://pointcept.github.io/Utonia/ 👉Repo https://github.com/Pointcept/Utonia

🍓Fully Offline Mobile-VTON🍓 👉A novel, hq, privacy-preserving framework that enables fully offline virtual try-on on commodity mobile devices using only a single user image and a garment image. Repo announced, to be released💙 👉Review https://t.ly/dsrIn 👉Paper arxiv.org/pdf/2603.00947 👉Project zhenchenwan.github.io/Mobile-VTON/ 👉Repo https://github.com/tmllab/2026_CVPR_Mobile-VTON

🦜Geometry-Aware 4D Head🦜 👉 GeoDiff4D is a novel framework that reconstructs animatable 4D head avatars from a single portrait image through geometry-aware diffusion. Code announced💙 👉Review https://t.ly/J9L-t 👉Paper https://lnkd.in/ddpv-78g 👉Project https://lnkd.in/d-vhukyj 👉Repo https://lnkd.in/dzd6mnFv

🧱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/

🫸 World-Grounded Hand-Object🫸 👉Given SLAMed egocentric videos, unlike existing methods that predict either hands or object poses separately, 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

🔥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

🚤Video Neural Compression🚤 👉TeCoNeRV by UMD is a framework for adapting INR hypernetworks to compress videos efficiently at higher resolutions. Impressive results: +5.35dB PSNR @720p on UVG, -36% bitrates & 1.5-3× faster encoding. Code announced💙 👉Review https://t.ly/0AtCK 👉Paper arxiv.org/pdf/2602.16711 👉Project namithap10.github.io/teconerv/ 👉Repo github.com/namithap10/TeCoNeRV/

🐙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

AI with Papers - Artificial Intelligence & Deep Learning - Telegram 频道 @ai_deeplearning 的统计与分析