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
显示更多📈 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 17 260 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 17 260 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。
17 260
订阅者
-224 小时
+67 天
+24230 天
帖子存档
🌲 MagicEdit: Magic Video Editing 🌲
👉MagicEdit: explicit disentangling the learning of content, structure & motion for Hi-Fi and temporally coherent video editing.
😎Report https://t.ly/tREX4
😎Paper https://arxiv.org/pdf/2308.14749.pdf
😎Project https://magic-edit.github.io/
😎Code github.com/magic-research/magic-edit
🌲 MagicEdit: Magic Video Editing 🌲
👉MagicEdit: explicit disentangling the learning of content, structure & motion for Hi-Fi and temporally coherent video editing.
😎Report https://t.ly/tREX4
😎Paper https://arxiv.org/pdf/2308.14749.pdf
😎Project https://magic-edit.github.io/
😎Code github.com/magic-research/magic-edit
🪶 ReST: Multi-Camera MOT 🪶
👉Novel reconfigurable two-steps graph model for multi-camera multi object video tracking (MC-MOT)
😎Review https://t.ly/3C5tb
😎Paper arxiv.org/pdf/2308.13229.pdf
😎Code github.com/chengche6230/ReST
💡 Relighting NeRF 💡
👉Neural implicit radiance representation for free viewpoint relighting of an object lit by a moving point light
😎Review https://t.ly/J-3_L
😎Project nrhints.github.io
😎Code github.com/iamNCJ/NRHints
😎Paper nrhints.github.io/pdfs/nrhints-sig23.pdf
🐨 Watch Your Steps: Editing by Text 🐨
👉The novel SOTA in image & scene (text) editing via denoising diffusion models
😎Review https://t.ly/fv9wn
😎Paper arxiv.org/pdf/2308.08947.pdf
😎Project ashmrz.github.io/WatchYourSteps
🥕 Scenimefy: I-2-I for anime 🥕
👉S-Lab unveils a novel semi-supervised I-2-I translation framework + HD dataset for anime
😎Review https://t.ly/IsdEG
😎Paper arxiv.org/pdf/2308.12968.pdf
😎Code https://github.com/Yuxinn-J/Scenimefy
😎Project https://yuxinn-j.github.io/projects/Scenimefy.html
🌆 NeO360: NeRF for Sparse Outdoor 🌆
👉#Toyota (+GIT) unveils NeO360: 360◦ outdoor scenes from a single or a few posed RGB images
😎Review https://t.ly/JDJZg
😎Paper arxiv.org/pdf/2308.12967.pdf
😎Project zubair-irshad.github.io/projects/neo360.html
🌵 POCO: 3D HPS using Confidence 🌵
👉 Novel framework for HPS regression: #3D human body + confidence in a single feed-forward pass
😎Review https://t.ly/cDePe
😎Paper arxiv.org/pdf/2308.12965.pdf
😎Project https://poco.is.tue.mpg.de
🦠 Instance-Level Semantics of Cells 🦠
👉TYC: novel dataset for understanding instance-level semantics & motions of cells in microstructures
😎Review https://t.ly/y-4VZ
😎Paper arxiv.org/pdf/2308.12116.pdf
😎Project christophreich1996.github.io/tyc_dataset/
😎Code github.com/ChristophReich1996/TYC-Dataset
😎Data tudatalib.ulb.tu-darmstadt.de/handle/tudatalib/3930
Hello everybody,
a lot of you asked me to open the comments to better enjoy the posts. I want to follow your suggestion, hope this new mood likes you.
🔥 NO SPAM
🔥 NO COMMERCIAL
🔥 NO UNRESPECTFUL MESSAGEs
🧡JUST AI & SCIENCE
⚠️ BAN AT THE FIRST VIOLATION ⚠️
🕹️ CoDeF: Video Content Deformation Fields 🕹️
👉Content deformation field is a new type of video representation for video-editing tasks
😎Review https://t.ly/PIVl-
😎Paper arxiv.org/pdf/2308.07926.pdf
😎Project https://qiuyu96.github.io/CoDeF
😎Code https://github.com/qiuyu96/CoDeF
⚡️Feature Matching at Light Speed⚡️
👉LightGlue is a lightweight feature matcher with high accuracy and blazing fast inference
😎Review https://t.ly/jkecX
😎Paper arxiv.org/pdf/2306.13643.pdf
😎Code github.com/cvg/LightGlue
🥎 SportsMOT + MixSort = Sports MOT 🥎
👉Nanjing just released a MOT dataset for sports scenes + the SOTA code/model for tracking (MixSort)
😎Review https://t.ly/NHUxL
😎Paper arxiv.org/pdf/2304.05170.pdf
😎Project deeperaction.github.io/datasets/sportsmot.html
😎Code github.com/MCG-NJU/MixSort
🛒 Digital Twins for AutoRetail Checkout 🛒
👉From #Nvidia a novel approach for using 3D assets for training 2D detection and tracking model in AutoRetail Checkout
😎Review https://t.ly/Ea7kt
😎Paper arxiv.org/pdf/2308.09708.pdf
😎Code github.com/yorkeyao/Automated-Retail-Checkout
🌈 Tracking by Persistent Dynamic View Synthesis 🌈
👉Novel simultaneous addressing of dynamic scene novel-view synthesis + 6-DOF tracking of all dense scene elements
😎Review https://t.ly/Bc535
😎Paper arxiv.org/pdf/2308.09713.pdf
😎Project dynamic3dgaussians.github.io
😎Code github.com/JonathonLuiten/Dynamic3DGaussians
🔥The code is out!🔥
😎 Code https://github.com/NVlabs/neuralangelo
🐘 Controllable Synthetic Data (extending Image-Net) 🐘
👉#META's PUG, a new generation of interactive environments for representation learning. Extending Image-Net!
😎Review https://t.ly/nCYs0
😎Paper arxiv.org/pdf/2308.03977.pdf
😎Project pug.metademolab.com
😎Code github.com/facebookresearch/PUG
👩🚀 HD Avatar via Text & Pose 👩🚀
👉 Generating expressive #3D avatars from nothing but text descriptions & pose guidance
😎Review https://t.ly/wrSMH
😎Paper arxiv.org/pdf/2308.03610.pdf
😎Project avatarverse3d.github.io
🎨 I-Paint: Interactive Neural Painting 🎨
👉 Novel AI-powered tool to help artists in completing their artworks
😎Review https://t.ly/ELUb0
😎Paper arxiv.org/pdf/2307.16441.pdf
😎Project helia95.github.io/inp-website
😎Supp helia95.github.io/inp-website/supp_mat.html
