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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 17 262 名订阅者,在 技术与应用 类别中位列第 7 543,并在 马来西亚 地区排名第 2 144 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 17 262 名订阅者。

根据 26 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 250,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 17.43%。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 3 008 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 27 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。

17 262
订阅者
+124 小时
+97 天
+25030 天
帖子存档
🥤NanoSAM: SAM on low-cost boards🥤 👉NanoSAM is a Segment Anything variant capable of running in real-time on #NVIDIA Jetson Orin with TensorRT 😎Review https://t.ly/UErq_ 😎Tutorial https://github.com/NVIDIA-AI-IOT/nanosam

🪛 PACE: in-the-wild SOTA Motion 🪛 👉#Nvidia unveils the novel SOTA to estimate the human motion in a global scene from moving cams. Stunning results. 😎Review https://t.ly/20you 😎Project https://nvlabs.github.io/PACE 😎Paper https://arxiv.org/pdf/2310.13768.pdf

🧡 Rotoscoping Prince Of Persia (1985) 🧡 👉 A rare footage for the animation of Prince of Persia (1989). Damn Romantic. 😎 More https://t.ly/xJife

🍈 Cutie: VOS with heavy occlusions🍈 👉Cutie: novel VOS for challenging scenarios with heavy occlusions & distractors 😎Review https://t.ly/W3FR- 😎Paper arxiv.org/pdf/2310.12982.pdf 😎Project https://hkchengrex.com/Cutie 😎Code https://github.com/hkchengrex/Cutie

🛣️ Holistic Parking Detection (YOLO) 🛣️ 👉 One-step Holistic Parking Slot Network: a tailor-made adaptation of YOLOv4 algorithm for all-shaped parking slot detection 😎Review https://t.ly/2l4ZG 😎Paper arxiv.org/pdf/2310.11629.pdf

🍡4K4D: Real-Time 4D View at 4K🍡 👉THE new SOTA in view synthesis of dynamic 3D scenes at 4K resolution is out. 30x faster, up to 400 FPS. Nuts! 😎Review https://t.ly/6ddQh 😎Paper arxiv.org/pdf/2310.11448.pdf 😎Project zju3dv.github.io/4k4d/ 😎Code github.com/zju3dv/4K4D

😻 CatFLW: Cat Neural Landmarks 😻 👉Landmark convolution neural network-based model for cat faces 😎Review https://t.ly/Y3mQ
😻 CatFLW: Cat Neural Landmarks 😻 👉Landmark convolution neural network-based model for cat faces 😎Review https://t.ly/Y3mQ8 😎Paper arxiv.org/pdf/2305.04232.pdf 😎Dataset www.tech4animals.org/catflw

🌱 Pose-Format: All-in-One Pose 🌱 👉 Pose-format: a comprehensive toolkit designed for human pose: unified, flexible, and easy-to-use 😎Review https://t.ly/rFrhq 😎Paper arxiv.org/pdf/2310.09066.pdf 😎Code github.com/sign-language-processing/pose

👗👗 AG3D: SOTA #3D clothed avatars from 2D👗👗 👉The novel SOTA in adversarial generative model of realistic 3D people is out. 😎Review https://t.ly/vnJO7 😎Paper zj-dong.github.io/AG3D/assets/paper.pdf 😎Project https://zj-dong.github.io/AG3D 😎Code https://github.com/zj-dong/AG3D

🦹‍♀️ Snap's Hyper-Realistic Human 🦹‍♀️ 👉New diffusive #AI by Snap that generates in-the-wild human images with hyper-reali
🦹‍♀️ Snap's Hyper-Realistic Human 🦹‍♀️ 👉New diffusive #AI by Snap that generates in-the-wild human images with hyper-realism. Swipe the gallery, NUTS!👇 😎Gallery https://t.ly/cG74X 😎Paper arxiv.org/pdf/2310.08579.pdf 😎Project snap-research.github.io/HyperHuman 😎Code github.com/snap-research/HyperHuman

🙋 Full Human Motion 🙋 👉OmniControl by Google is novel framework for text-conditioned human motion generation model based on diffusion process 😎Review https://t.ly/F_0Ov 😎Paper arxiv.org/pdf/2310.08580.pdf 😎Project neu-vi.github.io/omnicontrol/

📊 TextPSG: PSG from Text 📊 👉A novel problem in #AI: Panoptic Scene Graph Generation from Purely Textual Descriptions (Capt
📊 TextPSG: PSG from Text 📊 👉A novel problem in #AI: Panoptic Scene Graph Generation from Purely Textual Descriptions (Caption-toPSG) 😎Review https://t.ly/UXEmk 😎Paper arxiv.org/pdf/2310.07056.pdf 😎Project vis-www.cs.umass.edu/TextPSG 😎Code github.com/chengyzhao/TextPSG

🏊 SwimXYZ: Synthetic Swimming 🏊 👉SwimXYZ: synthetic dataset for swimming, monocular videos annotated with ground truth 2D
🏊 SwimXYZ: Synthetic Swimming 🏊 👉SwimXYZ: synthetic dataset for swimming, monocular videos annotated with ground truth 2D and 3D joints

💚💙 Where Is OpenCV 5? 💙💚 👉On October 24th, the organization is launching a crowdfunding campaign to raise funds for #OpenCV 5 development. 👆me in 2005 during my thesis work about face tracking; up to 50x faster than the previous SOTA. No chance to did it without OpenCV library and support from the community. 🔥Support #OpenCV 5 to create the next-gen of researchers and scientists. More: https://t.ly/UTukV

🔥Visual-Math Q&A: MathVista is out! 🔥 👉 MathVista is the ultimate benchmark designed to amalgamate challenges from diverse
🔥Visual-Math Q&A: MathVista is out! 🔥 👉 MathVista is the ultimate benchmark designed to amalgamate challenges from diverse mathematical and visual tasks 😎Review https://t.ly/yfqHZ 😎Paper https://arxiv.org/pdf/2310.02255.pdf 😎Project https://mathvista.github.io/ 😎Code github.com/lupantech/MathVista

🌱 Making LLaMA See and Draw 🌱 👉Tencent #AI planted a SEED of Vision in Large Language Model. Making LLaMA see 'n' draw stuff. 😎Review https://t.ly/QiCAv 😎Paper arxiv.org/pdf/2310.01218.pdf 😎Code github.com/AILab-CVC/SEED

☕Decaf: 3D Face-Hand Interactions☕ 👉The first learning-based MoCap to track human hands interacting with human faces in #3D from single monocular RGB videos 😎Review https://t.ly/070Tj 😎Paper arxiv.org/pdf/2309.16670.pdf 😎Project vcai.mpi-inf.mpg.de/projects/Decaf

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🧱 Generating Scenes from Touch 🧱 👉#AI for synthesizing images from tactile signals (and vice versa) and apply it to a number of visuo-tactile synthesis tasks 😎Review https://t.ly/Gxr0L 😎Paper https://arxiv.org/pdf/2309.15117.pdf 😎Project https://fredfyyang.github.io/vision-from-touch 😎Code https://github.com/fredfyyang/vision-from-touch

🌮 OW Indoor Segmentation 🌮 👉3D-OWIS is a novel open-world 3D indoor instance segmentation method (with auto-labeling scheme) to separate known/unknown category labels 😎Review https://t.ly/-7ALf 😎Paper arxiv.org/pdf/2309.14338.pdf 😎Code github.com/aminebdj/3D-OWIS