اکنون در دسترس! پژوهش تلگرام ۲۰۲۵ — مهمترین بینشهای سال 
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
نمایش بیشتر📈 تحلیل کانال تلگرام AI with Papers - Artificial Intelligence & Deep Learning
کانال AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) در بخش زبانی انگلیسی بازیگری فعال است. در حال حاضر جامعه شامل 17 144 مشترک است و جایگاه 7 701 را در دسته فناوری و برنامهها و رتبه 2 225 را در منطقه ماليزيا دارد.
📊 شاخصهای مخاطب و پویایی
از زمان ایجاد در невідомо، پروژه رشد سریعی داشته و 17 144 مشترک جذب کرده است.
بر اساس آخرین دادهها در تاریخ 25 ژوئن, 2026، کانال فعالیت پایداری دارد. در ۳۰ روز گذشته تغییر اعضا برابر -186 و در ۲۴ ساعت گذشته برابر 3 بوده و همچنان دسترسی گستردهای حفظ شده است.
- وضعیت تأیید: تأیید نشده
- نرخ تعامل (ER): میانگین تعامل مخاطب 23.94% است و در ۲۴ ساعت نخست پس از انتشار، محتوا معمولاً 6.86% واکنش نسبت به کل مشترکان کسب میکند.
- دسترسی پستها: هر پست به طور میانگین 0 بازدید دریافت میکند. در اولین روز معمولاً 1 177 بازدید جمعآوری میشود.
- واکنشها و تعامل: مخاطبان بهطور فعال حمایت میکنند؛ میانگین واکنش به هر پست 0 است.
- علایق موضوعی: محتوا بر موضوعات کلیدی مانند framework, object, dataset, tba, depth تمرکز دارد.
📝 توضیح و سیاست محتوایی
نویسنده این فضا را محل بیان دیدگاههای شخصی توصیف میکند:
“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”
به لطف بهروزرسانیهای پرتکرار (آخرین داده در تاریخ 26 ژوئن, 2026)، کانال همواره بهروز و دارای دسترسی بالاست. تحلیلها نشان میدهد مخاطبان بهطور فعال با محتوا تعامل دارند و آن را به نقطه اثرگذاری مهم در دسته فناوری و برنامهها تبدیل کردهاند.
17 144
مشترکین
+324 ساعت
-367 روز
-18630 روز
آرشیو پست ها
🌪️ TimeLapse++: Video Temporal Pyramid🌪️
👉Multi-scale lens to view the passage of time: far beyond a "classic" timelapse
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Inspired by "old-school" spatial pyramids
✅Video Spectrogram to go through pyramid
✅Months/years of data in a few seconds!
✅Multi-temporal freq., no aliasing
More: https://bit.ly/3TKnYPS
🥑 DALL·E: Outpainting via #NLP 🥑
👉Extending any original image, creating large-scale images in any aspect ratio
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Extending an image beyond its borders
✅Visual elements in same style of the input
✅Driving the image "story" in new directions
✅Shadows, reflections & textures w/ context
More: https://bit.ly/3eoH8uD
🪨Controllable #3D Adversarial Face🪨
👉#Meta (+CMU) on decoupling identity/expression + granular control over expressions
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Supervised auto-enc. + GAN
✅UV texture maps + 3D faces
✅Control expression, saving ID
✅Code under X11 License
More: https://bit.ly/3AVE80q
🚗 Massive Dataset in Virtual Cities 🚗
👉Synthehicle: 7 hours of labeled material, 340 cams, 64 days, rain, dawn, & night scenes.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Multi-target multi-cam tracking
✅2D, 3D, segm. & depth annotations
✅Instance, semantic & panoptic segm.
✅340 clips, 64 scenes, 17 hrs, 4M BBs
More: https://bit.ly/3TArHiV
🧡 Avatarization in 90's. So Romantic 🧡
👉Making of the first #MortalKombat in early 90's
More: https://bit.ly/3wTSpJB
🍊StableFace: Talking Face Generation🍊
👉Analysis on motion jittering in 3D face generation (audio-in -> video-out)
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Motion jittering analysis for stability
✅Gaussian-based adaptive smoothing
✅Augmented erosions of neural renderer
✅Audio-fused generator for dependency
More: https://bit.ly/3Kt95gI
🎍#3D scene manipulation from 2D🎍
👉Reconstruct, decompose, manipulate & render 3D scenes in a single pipeline
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Unique 3D, non-occupied space from 2D
✅Inverse query algorithm for shapes
✅First synthetic dataset for 3D editing
More: https://bit.ly/3RlYhTY
🔵 Deep Saliency: driving the attention 🔵
👉Google unveils a family of operators to "drive" human saliency
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Editing image to drive Saliency
✅Transforms to hide distractors
✅Warping operator for distractor
✅GAN-op for less-saliency altern.
More: https://bit.ly/3KoQQc2
🔥 #AIwithPapers: we are 4,000+! 🔥
💙💛Lot of people joined, and we talked about #StableDiffusion only twice! Can't believe it.💙💛
😈 Invite your friends -> https://t.me/AI_DeepLearning
🔥IDOL (#CVPR2022 winner): code is out!🔥
👉IDOL for VIS: outperforming all online/offline methods, the new SOTA!
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Online usually inferior by >10AP
✅Online based on contrast-learning
✅Discriminative++ instance embeddings
✅Full exploiting history for stability
More https://bit.ly/3dXCDXw
🦉PANDORA: Polarized Neural Decomposition🦉
👉CIL lab unveils PANDORA: polarimetric inverse rendering approach via INR
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Geometry, reflectance & illumination
✅normal, signed distance field, mesh
✅Diffuse-specular separation
✅Hi-fI incident illumination
More https://bit.ly/3CzGp3F
🍈 #StableDiffusion archive is out🍈
👉Lexica art is a Stable Diffusion prompt search engine. Real-time, countless #stablediffusion results for everyone. I had fun with the GOAT, #Maradona.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Maradona scoring against a capybara...
✅A poster of space jam with Maradona...
✅Painting of Maradona very detailed...
✅Painting of Maradona in heaven...
More: https://bit.ly/3PTXHLH
🌐RelPose: Probabilistic Relative Pose🌐
👉A novel method for core component in #SLAM / NeRF-powered apps.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Core component of SfM/SLAM
✅Pre-processing for neural (NeRF)
✅Energy-based over rotations
✅SOTA on both seen/unseen objects
More: https://bit.ly/3T60TXw
🍈DeepBillboards: old-school trick for #VR🍈
👉DeepBillboards models a 3D object implicitly using neural net on the user’s viewing direction
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅#Google Brain +Tsukuba + Tokyo
✅Rendering at higher res., improving #VR
✅NeRF into interactive VR with accuracy++
✅NeRF (or any others) directly in #Unity
More: https://bit.ly/3CsTQ5y
🥭Massive GTA-V human dataset🥭
👉GTA-Human: outperforming SOTA with a purely synthetic training.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅600+ gender, age, ethnicity & clothing
✅20,000+ clips, variety of human activities
✅6 categories of location, different BGs
✅Occlusions, lighting, and weather system
More: https://bit.ly/3wpZyRD
🔥 KeypointNeRF: code is out! 🔥
👉KeypointNeRF by #Meta: "NeRF"-avatars
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Generalizable NeRF for virtual avatar
✅Sparse 3D keypoints for SOTA avatar
✅Novel unseen subjects from 2/3 views
✅"iPhone" captures for #metaverse
More: https://bit.ly/3pyl17e
🔥🔥UPDATE🔥🔥
Code Released: https://github.com/facebookresearch/KeypointNeRF
🥑 CLIP-based Neural Style Transfer 🥑
👉From #Nvidia a novel method for transferring the style to a #3D object
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Texture style for 3D by CLIP-ResNet50
✅Nearest-neighbor feature matching loss
✅CLIP-based loss extraction of textures
✅NNFM for multiple style pics / control
✅No source code or models available 😒
More: https://bit.ly/3c32dK5
🍏NeuMan: Human NeRF in the wild🍏
👉#Apple opens a novel human pose/view from just a single in-the-wild video
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅No extra devices/annotations
✅Both Human (novel poses) + Scene
✅E2E SMPL optimization + error-corr.
✅Applications such as "telegathering"
More: https://bit.ly/3K4iTO6
🧰 FGT: flow-guided inpainting 🧰
👉#Microsoft (+USTC) unveils FGT: flow-guided ViT for video inpainting 🤯
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅OF into transformer for attention++
✅Flow completion net w/ local feats.
✅Dual perspective spatial MHSA
✅Local attention with global content
More: https://bit.ly/3pk5J5S
