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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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 17 144 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 17 144 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。

17 144

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

17 138

🐍 Implicitron: "democratizing" NeRF🐍 👉#META opens a novel framework for NeRF-world in #PyTorch3D #pytorch 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Implicit representations (NeRF) / Render ✅RaySampler/PointSampler & more ✅NeRF’s MLP, IDR’s FF, SRN, etc. ✅Renderers: MEAR, LSTMRenderer, etc. More: https://bit.ly/3bPyJPJ

17 138

🔥Stable Diffusion on clips. INSANE🔥 👉The most advanced latent text-to-image DM. #RunwayML just announced is going to apply it on clips 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Latent DM on 512p from LAION-5B ✅Frozen CLIP ViT-L/14 text encoder ✅Lightweight, runs on a 10GB-GPU ✅Checkpoints only for research More: https://bit.ly/3QfkRx3

17 138

🔥🔥UPDATE🔥🔥 Code Released: https://github.com/google-research/jax3d/tree/main/jax3d/projects/mobilenerf

17 138

🍨 Scaling Neural Indoor Scene 🍨 👉Neural scene rendering for indoor: scalable in both training/rendering 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Neural scene rendering for indoor ✅#3D into tiles with MLPs to scale up ✅Parallel training of tile-based MLPs ✅View-indep. components (via surf-MLP) More: https://bit.ly/3bH94IX

17 138

🎰 Texturify: Neural Textures Generator 🎰 👉A step towards automated content creation. HQ textures directly on surface of 3D object 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅TUM + Max Planck + Apple 🍏 ✅Realistic, HQ textures from 2D pics ✅3D shape geometry, no 3D supervision ✅3D-aware surface-based generation net More: https://bit.ly/3BW7UUU

17 138

🪰 EasyMocap: Open Neural Mocap 🪰 👉EasyMocap: open-source marker-less mocap with novel view synthesis from RGB 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬 (of last paper added): ✅Editable free-viewpoint video ✅Layered neural representation of humans ✅Multi-pax -> instances, weakly-supervised ✅HQ neural representation of the humans ✅Addressing camera error by human poses More: https://bit.ly/3p6lUDO

17 138

🥇#NVIDIA wins SIGGRAPH's Best Paper🥇 👉Instant #NeRF awarded as a best paper at SIGGRAPH 2022! 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Speed-up of several orders of magnitude ✅HQ neural primitives in a matter of secs ✅Render in tens of milliseconds at 1080p ✅Source code and resources available! More: https://bit.ly/3Qt8c9D

17 138

🧊EPro-PnP: Persp-n-Points Detection🧊 👉EPro-PnP: probabilistic PnP layer for general e2e pose estimation 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Probabilistic PnP for general e2e pose ✅Top-tier in 6DoF by inserting into CDPN ✅Deformable accurate detection ✅2D-3D corresp. learned from scratch More: https://bit.ly/3BNPXYr

17 138

🎹🎹 Learning Piano in #AR 🎹🎹 👉PianoVision (on #META #Quest2) accelerates the piano learning via Passthrough #AR & hand tracking 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Sheet Insight to learn sight-read ✅MIDI keyboard connectivity ✅Air piano for no physical pianos ✅Multiplayer Music Instruction ✅PianoVision Music Hall in #VR More: https://bit.ly/3zYvwGX

17 138

🍑 World-Object Detection via ViT 🍑 👉Google unveils OWL-ViT: open-vocabulary detector based on ViTs 🤯 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅ViTs for Open-World Localization ✅Img-level to open-vocabulary detection ✅SOTA one-shot (img.cond.) detection More: https://bit.ly/3Sy3jOj

17 138

🔥PCVOS: clip-wise mask VOS🔥 👉PCVOS: new semi-supervised video object segmentation method 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Reformulating semi-supervised VOS ✅Novel per-clip inference perspective ✅Clip-wise operation on intra-clip ✅PCVOS: model for per-clip inference ✅New SOTA on multiple benchmarks More: https://bit.ly/3vJtmbz

17 138

☀️LocoProp: Neural Layers Composition☀️ 👉Google AI unveils LocoProp: novel neural paradigm for modular composition of layers. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Backprop++ via Local Loss Optimization ✅Layer-based w-reg, target output, loss ✅Multiple local update via first-order opt. ✅Superior performance and efficiency More: https://bit.ly/3Q40YJn

17 138

🔥🔥MultiNeRF: three NeRFs are out!🔥🔥 👉Google opens the code of three #cvpr2022 papers: Mip-NeRF 360, Ref-NeRF, RawNeRF 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Paper_1: Mip-NeRF 360 ✅Paper_2: Ref-NeRF ✅Paper_3: NeRF in the Dark More: https://bit.ly/3QjpRRc

17 138

🔥 MinVIS, a new SOTA is out 🔥 👉#Nvidia miniVIS: no video-based architectures nor training procedures🤯 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Video architecture/train not required ✅MinVIS outperforms the previous SOTA ✅Occluded VIS (OVIS): >10% improvement ✅1% of labeled frames >> fully-supervised More: https://bit.ly/3pcYzk1

17 138

🚀 #VR by NASA - 1985 🚀 👉Q: is #VR the technology that developed least in the last 40 years? 🤔 Let's talk: https://bit.ly/3JxDZ7i

17 138

👩‍🦰 Real-Time Neural Hair 👩‍🦰 👉Accurate hair geometry & appearance from multi-pics 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Bonn, CMU and Reality Labs ✅Photorealistic Real-Time render ✅HQ strand geometry/appearance ✅Novel scalp texture description ✅Intuitive manipulation of 3D hair More: https://bit.ly/3vBiH2G

17 138

🧣NeRF for Outdoor Scene Relighting🧣 👉NeRF-OSR: the first neural radiance fields approach for outdoor scene relighting 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅NeRF-method for outdoor relighting ✅Simultaneous illumination/viewpoint ✅Control over shading, shadow, albedo ✅Self-Supervised training from outdoor ✅Dataset: 3240 viewpoints, 110+ times More: https://bit.ly/3vBiH2G

17 138

🔥🔥UPDATE🔥🔥 Code Released: https://github.com/andreas128/RePaint

17 138

🔥 MobileNeRF is out -> Pure Fire! 🔥 👉MobileNeRF is out: the mobile evolution of NeRF via textured polygons. 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅Same quality, 10x faster than SNeRG ✅Memory-- by storing surface textures ✅Integrated GPUs: less memory/power ✅Suitable for browser & viewer is HTML More: https://bit.ly/3PUKPWy

17 138

🔥AND/OR: Composable Diffusion Models🔥 👉Novel neural compositional generation via Composable Diffusion Models 𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬: ✅DM as energy-based models ✅Connecting diffusion models ✅Conjunction & negation, on top of DM ✅Zero-shot combinatorial generalization More: https://bit.ly/3PYv1Cs