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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马来西亚2 225 技术与应用7 701...

📈 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 17 136 名订阅者，在 技术与应用 类别中位列第 7 701，并在 马来西亚 地区排名第 2 225 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 17 136 名订阅者。

根据 25 六月, 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 -186，过去 24 小时变化为 3，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 23.94%。内容发布后 24 小时内通常能获得 6.86% 的反应，占订阅者总量。
帖子覆盖： 每篇帖子平均可获得 0 次浏览，首日通常累积 1 177 次浏览。
互动与反馈： 受众积极参与，单帖平均反应数为 0。
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 六月, 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。

17 136

订阅者

+324 小时

-367 天

-18630 天

4 105

帖子浏览量

~ 1 17724 小时

~ 1 35348 小时

23.94%

参与率

无数据

每日帖子数

Ads index

beta

帖子存档

17 136

🦑Big Egocentric Dataset by #Meta 🦑 👉Novel dataset to speed-up research on egocentric MR/AI 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅159 sequences, multiple sensors ✅Scenarios: cooking, exercising, etc. ✅‘Desktop Activities’ via multi-view mocap ✅Dataset available upon request More: https://bit.ly/3QDccVW

17 136

🐠Largest Dataset for #autonomousdriving🐠 👉SHIFT: largest synthetic dataset for #selfdrivingcars. Shifts in cloud, rain, fog, time of day, vehicle & pedestrian density🤯 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅4,800+ clips, multi-view sensor suite ✅Semantic/instance, M/stereo depth ✅2D/3D object detection, MOT ✅Optical flow, point cloud registration ✅Visual-Odo, trajectory & human pose More: https://bit.ly/3HJBUUT

17 136

🍅Segmentation with INSANE Occlusions🍅 👉CMU unveils WALT: segmenting in severe occlusion scenarios. Performance over human. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅WALT: Watch & Learn Time-lapse ✅4K/1080p cams on streets over a year ✅Performance over human-supervised ✅Object-occluder-occluded neural layers ✅Source code under MIT license More: https://bit.ly/3n7pvjO

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🔥 #AIwithPapers: we are 2,900+! 🔥 💙💛 Cheers from "Black Metal Lady Gaga" plotted by DallE-mini 💙💛 😈 Invite your friends -> https://t.me/AI_DeepLearning

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✋HaGRID : Half Million Hands👋 👉Russian Sberbank opens HaGRID, enormous dataset for HGR. "Peace" label is present 🔵🟡 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅552,992 samples, 18 classes ✅HD resolution in RGB format ✅BBox, gesture, leading hands ✅Dataset/models available More: https://bit.ly/3n2cd8r

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🦕 SAVi++: Segmentation by #Google 🦕 👉Novel unsupervised object-centric #AI to predict depth signals from slot-based video representation 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Segmenting complex dynamic scenes ✅Static/Moving objects on naturalistic BG ✅LiDAR-SAVi: segmenting in the wild ✅Source code and model soon available! More: https://bit.ly/3n3hywd

17 136

🧠 Bias in #AI, explained simple 🧠 👉Asking DallE-Mini to help me to show what the BIAS in #AI is 𝐆𝐞𝐧𝐞𝐫𝐚𝐭𝐞𝐝 𝐒𝐚𝐦𝐩𝐥𝐞𝐬: ✅Best eng.->men/Caucasians ✅Best doctors->men/Caucasians ✅Top CEOs->men/Caucasians ✅Chef, kitchen->men/Caucasians ✅Rich People->only Caucasians ✅Poor People->non-Caucasians ✅Italian engineers->back in 30's ✅Chinese eng.->infrastructures ✅Italian working->local market ✅Chinese working->vegetables ✅Men workers->constructions ✅Women workers->only office More: https://bit.ly/3b0UFqd

17 136

🏄🏻‍♀️Neural Super-Resolution in Movies🏄🏻‍♀️ 👉Implicit neural representation to get arbitrary spatial resolution & FPS -> Super Resolution! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Video as continuous video representation ✅Clips in arbitrary space/time resolution ✅OOD generalization in space-time ✅Source code and models available More: https://bit.ly/3xsqccf

17 136

🐹 NOAH just open-sourced! 🐹 👉A novel approach to find the optimal design of prompt modules through NAS algos. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅NOAH from Neural prOmpt seArcH ✅Parameter-efficient “prompt modules” ✅Efficient NAS-based implementation ✅Better than transfer, few-shot & domain gen. More: https://bit.ly/3MKfVhi

17 136

👗BodyMap: Hyper-Detailed Humans👗 👉#META unveils 1st-ever dense continuous correspondence for clothed humans 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅1st-ever dense continuous corresp. ✅HQ fingers, hair, and clothes ✅Novel ViT-based architecture ✅SOTA on DensePose COCO More: https://bit.ly/39nEPps

17 136

🧨 Scaling Transformers to GigaPixels!🧨 👉Novel ViT called Hierarchical Image Pyramid Transformer (HIPT) -> Scaling to GigaPixels! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Gigapixel whole-slide imaging (WSI) ✅Leveraging natural hier. structure of WSI ✅Self-supervised Hi-Res representations ✅Source code and models available! More: https://bit.ly/3xLuzkg

17 136

🔥One Millisecond Backbone. Fire!🔥 👉MobileOne by #Apple: efficient mobile backbone with inference <1 ms on #iPhone12! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅75.9% top-1 accuracy on ImageNet ✅38× faster than MobileFormer net ✅Classification, detection & segmentation ✅Source code & model soon available! More: https://bit.ly/3tsT7f2

17 136

🎒 EG3D: source code is out! 🎒 👉#Nvidia just opened EG3D: real time multi-view faces w/ HQ #3D geometry! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Tri-plane-based 3D GAN framework ✅Pose-correlated attribute (expression) ✅SOTA in uncond. 3D-aware synthesis ✅Source code & models NOW available! More: https://bit.ly/3aOfHs0

17 136

🏖️ HumanNeRF: source code is out! 🏖️ 👉Pausing the video at any frame and rendering the subject from arbitrary views! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Synthesizing photorealistic humans ✅Synthesizing details, ie. cloth & face ✅Volumetric canonical T-pose ✅Skeletal rigid/non-rigid decomposition More: https://bit.ly/3NEkTNY

17 136

⚽ Zero to #Messi with #deeplearning ⚽ 👉EA unveils a neural system to learn multiple soccer juggling skills 😍 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Learning difficult soccer juggling skills ✅Layer-wise mixture-of-experts architecture ✅Specialization arises naturally ✅Adaptive random walk training strategy More: https://bit.ly/3mwRaL2

17 136

🏇🏻Neural Clips by #Nvidia: INSANE 🏇🏻 👉Neural generation with changes in camera viewpoint & content that arises over time 🤯 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Novel hierarchical generator architecture ✅Temp. receptive field + temporal embed. ✅Multi-res. with super-resolution network ✅SOTA in long clip with motion & changes ✅Code, data & models in August 2022 🏖️ More: https://bit.ly/3zroWsC

17 136

🍏 Open Source Vision from #Apple 🍏 👉CVNets: open-source (not a joke) lib for neural vision. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅PyTorch-based neural lib. for vision ✅Train 2−4× longer w/ augmentations ✅Plug-and-play components for CV ✅Source code under a custom license More: https://bit.ly/39d1dSj

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🔴 Geogram: geometric algos in C++ 🔴 👉Novel open-source programming library with (research) geometric algorithms in C++ 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Geometry Processing from #INRIA ✅30+ papers from SIGGRAPH, etc. ✅Grants: GOODSHAPE & VORPALINE ✅Code (mostly C++) under BSD 3 More: https://bit.ly/3mhS4L7

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🧘🏻‍♂️YogNet: neural yoga assistant🧘🏻‍♂️ 👉Multi-person yoga neural expert for 20 asanas 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅CNNs & reg.LSTMs + 3D-CNNs ✅Multi-person asanas in real-time ✅YAR: dataset for yoga & posture ✅1206 videos, 2D RGB camera More: https://bit.ly/3NncVbE

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🐢 Transformer-Based Sens-Fusion 🐢 👉Updating TransFuser (CVPR21): image + LiDAR representations with self-attention 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Existing approach can't handle traffic 😢 ✅Novel multi-modal fusion transformer ✅The new SOTA in driving performance ✅Reducing avg collisions per KM by 48% ✅Insights on current limitations of E2E More: https://bit.ly/391dmd6