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
Ko'proq ko'rsatish📈 Telegram kanali AI with Papers - Artificial Intelligence & Deep Learning analitikasi
AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) Ingliz til segmentidagi kanali faol ishtirokchi. Hozirda hamjamiyat 17 261 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 532-o'rinni va Malayziya mintaqasida 2 128-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 17 261 obunachiga ega bo‘ldi.
29 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 219 ga, so‘nggi 24 soatda esa 0 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.
- Tasdiqlash holati: Tasdiqlanmagan
- Jalb etish (ER): Auditoriya o‘rtacha 16.46% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.09% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 2 842 marta ko‘riladi; birinchi sutkada odatda 1 223 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 17 ta reaksiya keladi.
- Tematik yo‘nalishlar: Kontent framework, object, dataset, tba, depth kabi asosiy mavzularga jamlangan.
📝 Tavsif va kontent siyosati
Muallif resursni shaxsiy fikrni ifoda etish maydoni sifatida ta’riflaydi:
“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”
Yuqori yangilanish chastotasi (oxirgi ma’lumot 30 Oktabr, 2026 da olingan) sababli kanal doimo dolzarb va katta qamrovli bo‘lib qoladi. Analitika auditoriya kontent bilan faol hamkorlik qilishini, uni Texnologiyalar & Aralashmalar toifasidagi muhim ta’sir nuqtasiga aylantirishini ko‘rsatadi.
17 261
Obunachilar
Ma'lumot yo'q24 soatlar
+27 kun
+21930 kun
Postlar arxiv
💜 #Selfdriving in 80's. Damn Romantic 💜
👉The first self-driving car with people on board, 1986. So slow and lovely.
More: https://bit.ly/3BtRDon
🥤K-VIL: Keypoint-based visual imitation🥤
👉K-VIL: auto-incremental extraction of object-centric task representation.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Efficient task-relevant keypoints
✅Embodiment-independent tasks
✅Adaptation of tasks to new scenes
✅Input: only a small set of demo clips
✅Novel keypoint-based controller
More: https://bit.ly/3eIrxpP
🐲 Open-Source Self-Driving projects 🐲
👉A free repo with many autonomous vehicle-related projects
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Basic/Advance Lane/Line Detection
✅Driving behavior by training & validating
✅Autopilot: predicting steering angle
More: https://bit.ly/3qqJ7RB
🎪 SOTA in Arbitrary Shape Text Detection 🎪
👉Novel unified coarse-to-fine Transformer for arbitrary shape text detection
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Coarse-to-fine arbitrary text detection
✅Accurate text detection, NO post-process
✅Boundary proposal generation mechanism
✅Innovative boundary transformer (iterative)
✅Boundary energy loss (BEL) for refinement
More: https://bit.ly/3D6Ryt4
👹TT-GNeRF: generative NeRF for Faces👹
👉TT-GNeRF: a novel 3D-aware GANs based on generative NeRF for faces
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅ETH + Uni_Trento + #Snap 🤯
✅DAEM for disentanglement of 3D model
✅"Training-as-Init, Optimizing-for-Tuning"
✅Consistency++, preserving non-target ROI
✅Unsupervised optimization of geometry
More: https://bit.ly/3ARZmMw
🌈 X-NeRF: Cross-Spectral NeRF 🌈
👉Cross-Spectral NeRF from cams with different light spectrums
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅First ever cross-spectral NeRF
✅Avoiding non-trivial calib/match
✅Normalized Cross-Device Coords
✅Novel dataset w/ RGB, MS, & IR
More: https://bit.ly/3RqHnUo
🐠VIS - Deformable Transformers 🐠
👉DeVIS: VIS method with efficiency and performance of deformable ViT
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Temp. multi-scale D-Attention
✅Instance-aware object queries
✅Mask: DA + multi-scale feats map
✅Improved multi-cue clip tracking
✅SOTA on YouTube-VIS 2021/OVIS
More: https://bit.ly/3TQv1Xc
🤯 #StableDiffusion + #Dallemini = BOOM! 🤯
👉A #colab notebook that combines Stable Diffusion + DALL-E Mini (Craiyon)
More: https://bit.ly/3TTOshR
🦎 VMT: Video Mask Transfiner 🦎
👉Novel highly efficient ViT structure for video instance segmentation.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅HD & more temporally stable mask
✅Higher resolution features for VIS
✅Detecting error-prone s-t. regions
✅Auto-refinement on training data!
More: https://bit.ly/3RKXtb4
🫐 Stable Diffusion Video is out! 🫐
👉A free notebook to generate videos by interpolating the latent space of SD.
𝐇𝐢𝐠𝐡𝐥𝐢𝐠𝐡𝐭𝐬:
✅Blueberry to strawberry spaghetti
✅Dream items from same prompt
✅Morph different prompts (seeds)
✅Built on a script by A. Karpathy
More: https://bit.ly/3ey8632
🌪️ 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
