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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 17 259 名订阅者,在 技术与应用 类别中位列第 7 509,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 17 259 名订阅者。

根据 25 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 261,过去 24 小时变化为 2,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 16.91%。内容发布后 24 小时内通常能获得 7.04% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 918 次浏览,首日通常累积 1 216 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 16。
  • 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 26 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。

17 259
订阅者
+224 小时
+17 天
+26130 天
帖子存档
🖲️ Amodal Tracking Any Object 🖲️ 👉Amodal tracking": inferring complete object boundaries, even when certain portions are occluded. New benchmark & approach, 2x better than SOTA in people tracking 🔥 👉Review https://t.ly/Rc6Ku 👉Paper https://lnkd.in/d39rFYT4 👉Project https://lnkd.in/d7bkEcni 👉(empty) Repo https://lnkd.in/dTsNKdfz

🧊 ControlNet for Depth Conditioning 🧊 👉KAUST (+ #Adobe) unveils LooseControl to control the generative image modeling process. Layout by boundaries and #3D box control via object locations (approximate bounding boxes). A step forward in generative design of the products. #artificialintelligence #machinelearning #ml #AI #deeplearning #computervision #AIwithPapers #metaverse 👉Review https://t.ly/9y72m 👉Paper https://arxiv.org/pdf/2312.03079.pdf 👉Project https://shariqfarooq123.github.io/loose-control/ 👉Demo🤗 https://huggingface.co/spaces/shariqfarooq/LooseControl 👉Repo https://github.com/shariqfarooq123/LooseControl

🔥 #AIwithPapers: we are 8k+ 🔥 👉 After flirting with #ChatGpt for months, you back in love with this channel and #ComputerV
🔥 #AIwithPapers: we are 8k+ 🔥 👉 After flirting with #ChatGpt for months, you back in love with this channel and #ComputerVision. I felt bad but I forgive you 🧡 😈 What about boosting us channel? Click: https://t.me/AI_DeepLearning?boost 😈Invite -> https://t.me/AI_DeepLearning

💃Outfit Anyone: Ultra-HQ VTO💃 👉Alibaba unveils Outfit Anyone: a two-stream conditional diffusion able to adeptly handle garment deformation for more lifelike results in VOT. Extra: Outfit Anyone + Animate Anyone for outfit + motion generation of any character. NO CODE / NO PAPER / DEMO AVAILABLE :) 👉Review https://t.ly/o6UR9 👉Demo https://lnkd.in/dpQYdXhc 👉Repo (empty) https://lnkd.in/dBsNST6r

🪼 PatchFusion: SOTA Mono-Depth 🪼 👉PatchFusion: novel end-to-end tile-based framework for hi-res monocular metric depth estimation. It's the new SOTA in metric depth estimation from mono. Code & Demo on Hugging Face able 🔥 👉Review https://t.ly/hv3yT 👉Paper https://lnkd.in/d9dXP7iP 👉Project https://lnkd.in/dQcvVJSx 👉Repo https://lnkd.in/dW2GdVR5 👉Demo https://lnkd.in/dFW-gAiY

📲 EdgeSAM: On-Device 40x SAM 📲 👉A novel hyper-optimized version of SAM for mobile devices such as #Iphone. Pure CNNs backbone (better suitable for ANE), up to 40x faster! 👉Review https://t.ly/m_vLH 👉Paper https://lnkd.in/gHZVZN2x 👉Project https://lnkd.in/gK8qEK8p 👉Repo https://lnkd.in/gj6YAGNv 👉Hugging Face https://lnkd.in/gUUHJvxz

🪩 DreaMoving: Human Generation 🪩 👉Alibaba strikes again with DreaMoving: a diffusion-based controllable video generation framework to produce HQ customized human videos. 👉Review https://t.ly/BD_Yf 👉Paper https://lnkd.in/gepP6Rjw 👉Project https://lnkd.in/gwm72cfS 👉Repo (empty) https://lnkd.in/gsc2Qt-F

🫶 #3D Hands with Transformers 🫶 👉 HaMeR is a robust and accurate Hand Mesh Recovery from images and video frames, based on Transformer architecture. It's the new SOTA. 👉Review https://t.ly/YtAW8 👉Paper https://arxiv.org/pdf/2312.05251.pdf 👉Project https://geopavlakos.github.io/hamer 👉Demo huggingface.co/spaces/geopavlakos/HaMeR 👉Colab colab.research.google.com/drive/1rQbQzegFWGVOm1n1d-S6koOWDo7F2ucu

🔥 EfficientSAM: 20x faster Segment Anything 🔥 👉Meta AI Research unveils a novel family of SAM-like models, light-weight SAM models with SOTA quality-efficiency trade-offs. Up to 20x faster! 👉Review https://t.ly/966QS 👉Paper https://lnkd.in/duijp_Rh 👉Project https://lnkd.in/dW-p2CuH 👉Code https://lnkd.in/dAbZaB2t 👉Demo https://lnkd.in/d-tjKiUd

🩰 Magic Animating Human 🩰 👉MagicAnimate: the new SOTA in human animation. Code available: let's dance! 👉Review https://t.ly/Oq7Za 👉Paper https://lnkd.in/dSUbGgCs 👉Project https://lnkd.in/dkVFf-SV 👉Code https://lnkd.in/dj2dbzdg 👉Demo https://lnkd.in/dHEKPE9q

Hello everybody, a lot of you asked me to re-open the sharing of the contents to involve more people. I want to follow your suggestion, hope you will enjoy this new mood! 👍 FREE TO FORWARD TO OTHER TELEGRAM CHANNELS 🔥 NO COPY OF THE POSTS 🔥 NO COMMERCIAL USAGE 🔥 NO UNRESPECTFUL USAGE ⚠️ UNDO THE FORWARDING OPTION AT THE FIRST VIOLATION ⚠️

🔎 Generative Powers of Ten 🔍 👉A text-to-image model to generate consistent content across multiple image scales, enabling extreme semantic zooms into a scene. From universe to a human cell 🤯 👉Review https://t.ly/2DG44 👉Paper https://lnkd.in/eDcSpU59 👉Project https://lnkd.in/e6NKu8n9

🍡 Animate Anyone: new SOTA! 🍡 👉Alibaba unveils Animate Anyone: novel #AI for transforming character images into animated videos controlled by desired pose sequences. Animating any character image into a video, unconstrained by specific domains 🚀 👉Review https://t.ly/qCahZ 👉Paper https://lnkd.in/d-zi8EZ6 👉Project https://lnkd.in/djwjQRvq 👉Code https://lnkd.in/dDMkjnKz

👑 HD Generative #AI With No $$$ 👑 👉DemoFusion: a novel approach for HD image generation w/ no money. Progressive Upscaling, Skip Residual, & Dilated Sampling to achieve higher-resolution ever 🔥 👉Review https://t.ly/sIqDV 👉Paper https://lnkd.in/deDt-zcK 👉Project https://lnkd.in/dFGj47Xw 👉Code https://lnkd.in/dY3UcXwp

🧱 Material Palette from Images 🧱 👉A novel problem in #AI: material extraction from a real-world image without any prior knowledge 🤯 👉Discussion https://t.ly/AIWs- 👉Paper https://lnkd.in/dBFAVWPF 👉Project https://lnkd.in/dV5jK8Sm 👉Code https://lnkd.in/dNhMnfFb 👉Dataset (coming) ...

🌳 NebulOS: (more than) Green AI 🌳 👉A novel hardware-aware Training-Free NAS approach that considers both training-free metrics & HW constraints, aiming to find the optimal balance between validation accuracy & energy consumption. 🚀 👉Review https://t.ly/Ozso1 👉Project sites.google.com/view/nebulos 👉Code https://github.com/fracapuano/NebulOS 👉Video https://lnkd.in/exN4Q2Fu 👉Hugging Face demo https://lnkd.in/eyCcPEPc

🎡 Panoptic Video Scene Graph 🎡 👉Combining video scene graph generation w/ panoptic segmentation for holistic video understanding. Novel HQ dataset with fine, temporal scene graph annotations & panoptic segmentation. Code released!🔥 👉Review https://t.ly/tckDT 👉Project jingkang50.github.io/PVSG/ 👉Paper arxiv.org/pdf/2311.17058.pdf 👉Code github.com/LilyDaytoy/OpenPVSG 👉Tool github.com/lilyDaytoy/PVSGAnnotation

🔥 Stable (Stability.AI) Video Diffusion 🔥 👉 #StabilityAI released Stable Video Diffusion: latent video diffusion model for high-resolution, SOTA text-to-video and image-to-video generation 👉 Review https://t.ly/XwHys 👉 Code https://lnkd.in/dQw_yNuV 👉 Paper https://lnkd.in/dHn6f787

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