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AI with Papers - Artificial Intelligence & Deep Learning

AI with Papers - Artificial Intelligence & Deep Learning

前往频道在 Telegram

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 7 540,并在 马来西亚 地区排名第 2 147 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 27 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 242,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 16.94%。内容发布后 24 小时内通常能获得 7.10% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 923 次浏览,首日通常累积 1 225 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 28 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
-224 小时
+67 天
+24230 天
帖子存档
🪁 VoxFormer: 2D->#3D Voxel Transformer 🪁 👉#Nvidia VoxFormer: transformer for #3D volumetric semantics from 2D images 😎Paper arxiv.org/pdf/2302.12251.pdf 😎Code github.com/NVlabs/VoxFormer

🫳 Neural Relighting of Hands 🫴 👉#META unveil the first neural relighting for personalized hands in real-time under novel illumination 😎Review https://bit.ly/3SblmKC 😎Paper arxiv.org/pdf/2302.04866.pdf 😎Project sh8.io/#/relightable_hands

🏀 #NBA Mixed Reality is NUTS 🏀 👉The premiere of the streaming app of the #NBA is totally INSANE. A mix of #AI, CG and much
🏀 #NBA Mixed Reality is NUTS 🏀 👉The premiere of the streaming app of the #NBA is totally INSANE. A mix of #AI, CG and much more👇 🏀More: https://bit.ly/3IJ3uUp

🛡️ TPV: Tesla's O-Net competitor 🛡️ 👉From Beijing an open-source approach for vision-centric autonomous driving #3D perception 😎Review https://bit.ly/3lNvVYc 😎Paper arxiv.org/pdf/2302.07817.pdf 😎Code github.com/wzzheng/TPVFormer

🌶️ 3D-aware conditional generative AI 🌶️ 👉 Pix2Pix3D: 3D-aware conditional generative AI for controllable photorealistic synthesis 😎Review https://bit.ly/3I80MWS 😎Paper arxiv.org/pdf/2302.08509.pdf 😎Project www.cs.cmu.edu/~pix2pix3D 😎Code github.com/dunbar12138/pix2pix3D

🦩 One-Shot Face via LSs of StyleGAN2 🦩 👉 Novel video generation framework with edits, facial motions, deformations & identity 😎Review https://bit.ly/3xuChhF 😎Paper arxiv.org/pdf/2302.07848.pdf 😎Project trevineoorloff.github.io/FaceVideoReenactment_HybridLatents.io/

📬 DIVOTrack: crossview MOT dataset 📬 👉 DIVOTrack + CrossMOT: the ultimate solution for MOT in realistic scenario 😎Review https://bit.ly/3YSFZgL 😎Paper arxiv.org/pdf/2302.07676.pdf 😎Code github.com/shengyuhao/DIVOTrack

🦞 SOTA ALERT: YOWOv2 is out! 🦞 👉 The 2nd-gen of YOWO, real-time detection of spatio-temporal action 😎Review https://bit.ly/3IscY60 😎Paper arxiv.org/pdf/2302.06848v1.pdf 😎Code github.com/yjh0410/YOWOv2

🌅 Novel semantics-guided natural synthesis 🌅 👉Alibaba #AI unveils a novel semantics-guided view synthesis of natural scenes 😎Review https://bit.ly/4115MVJ 😎Paper arxiv.org/pdf/2302.07224.pdf 😎Project zju3dv.github.io/paintingnature

🌅 Novel semantics-guided natural synthesis 🌅 👉Alibaba #AI unveils a novel semantics-guided view synthesis of natural scenes

💘 3D-aware Blending via Generative NeRF 💘 👉Novel 3D-aware blending method via generative NeRFs 😎Review https://bit.ly/3lBEJA2 😎Paper arxiv.org/pdf/2302.06608.pdf 😎Project blandocs.github.io/blendnerf 😎Code github.com/naver-ai/BlendNeRF

🥸 MEGANE: Generative Morphable Eyeglass 🥸 👉#META unveils the most advanced #3D compositional morphable AI for eyeglasses (HD geometry/photometric interaction) 😎Review https://bit.ly/3jOWifu 😎Paper arxiv.org/pdf/2302.04868.pdf 😎Project junxuan-li.github.io/megane

🎃 In-N-Out: 3D-aware OOD video editing 🎃 👉Novel 3D-aware video editing able to manipulate OOD objects (e.g. heavy makeup, accessories) 😎Review https://bit.ly/3jN0CMu 😎Paper arxiv.org/pdf/2302.04871.pdf 😎Project https://in-n-out-3d.github.io

🧱 LEGO-Net: Objects in Rooms 🧱 👉Transformer-based iterative method for rearrangement of objects in messy rooms 😎Review https://bit.ly/3HR0fs6 😎Paper arxiv.org/pdf/2301.09629.pdf 😎Project ivl.cs.brown.edu/#/projects/lego-net

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles 😎Review https://bit.ly/3HJubXg 😎Paper arxiv.org/pdf/2302.01110.pdf 😎Code github.com/hnuzhy/DirectMHP

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles 😎Review https://bit.ly/3HJubXg 😎Paper arxiv.org/pdf/2302.01110.pdf 😎Code github.com/hnuzhy/DirectMHP

🗿DirectMHP: Multi-Head Pose Estimation🗿 👉Novel E2E multi-person head pose estimation (MPHPE) under full-range angles

🌘 Gen-1: next-gen Generative #AI 🌘 👉#Runaway unveils Gen-1: the next step forward for Generative AI. Registration available for beta -> hurry up! 😎Review https://bit.ly/3YqQYh8 😎Project https://research.runwayml.com/gen1

🦚 MOSE: coMplex video Object SEgmentation 🦚 👉Novel Dataset for VOS is out! SOTA method on DAVIS is only 59.4% on MOSE 😎Review https://bit.ly/40yzSzW 😎Paper arxiv.org/pdf/2302.01872.pdf 😎Project henghuiding.github.io/MOSE/ 😎Code github.com/henghuiding/MOSE-api

🧩 Text-Guided #3D Texturing 🧩 👉 Text-Guided HQ textures via iterative diffusion-based process 😎Review https://bit.ly/3ldC6Ez 😎Project texturepaper.github.io/TEXTurePaper 😎Code github.com/TEXTurePaper/TEXTurePaper 😎Paper texturepaper.github.io/TEXTurePaper/static/paper.pdf