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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Малайзия2 225 Технологии и приложения7 701...

📈 Аналитический обзор Telegram-канала AI with Papers - Artificial Intelligence & Deep Learning

Канал AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) языкового сегмента Английский является активным участником. Сейчас сообщество объединяет 17 144 подписчиков, занимая 7 701 место в категории Технологии и приложения и 2 225 место в регионе Малайзия.

📊 Показатели аудитории и динамика

С момента создания невідомо проект демонстрирует стремительный рост, собрав аудиторию из 17 144 подписчиков.

Согласно последним данным от 25 июня, 2026, канал показывает стабильную активность. За последние 30 дней изменение числа участников составило -186, а за последние 24 часа — 3, при этом общий охват остаётся высоким.

Статус верификации: Не верифицирован
Уровень вовлечённости (ER): Средний показатель вовлечённости аудитории составляет 23.94%. В первые 24 часа после публикации контент обычно набирает 6.86% реакций от общего числа подписчиков.
Охват публикаций: В среднем каждый пост получает 0 просмотров. В течение первых суток публикация набирает 1 177 просмотров.
Реакции и взаимодействия: Аудитория активно поддерживает контент: среднее количество реакций на один пост — 0.
Тематические интересы: Контент сосредоточен на ключевых темах, таких как framework, object, dataset, tba, depth.

📝 Описание и контентная политика

Автор описывает ресурс как площадку для выражения субъективного мнения:
“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”

Благодаря высокой частоте обновлений (последние данные получены 26 июня, 2026) канал поддерживает актуальность и высокий уровень охвата публикаций. Аналитика показывает, что аудитория активно взаимодействует с контентом, что делает его важной точкой влияния в категории Технологии и приложения.

17 144

Подписчики

+324 часа

-367 дней

-18630 день

4 105

Просмотры поста

~ 1 17724 часа

~ 1 35348 часов

23.94%

Коэффициент вовлеченности

Нет данных

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Архив постов

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