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AI with Papers - Artificial Intelligence & Deep Learning

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 7 500-o'rinni va Malayziya mintaqasida 2 124-o'rinni egallagan.

📊 Auditoriya ko‘rsatkichlari va dinamika

невідомо sanasidan buyon loyiha tez o‘sib, 17 261 obunachiga ega bo‘ldi.

24 Oktabr, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni 258 ga, so‘nggi 24 soatda esa -2 ga o‘zgardi va umumiy qamrov yuqori darajada qolmoqda.

  • Tasdiqlash holati: Tasdiqlanmagan
  • Jalb etish (ER): Auditoriya o‘rtacha 16.76% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining 7.11% ini tashkil etuvchi reaksiyalarni to‘playdi.
  • Post qamrovi: Har bir post o‘rtacha 2 893 marta ko‘riladi; birinchi sutkada odatda 1 227 ta ko‘rish yig‘iladi.
  • Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 16 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 25 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
-224 soatlar
+27 kun
+25830 kun
Postlar arxiv
🌏 JoyHallo: Mandarin Digital Human 🌏 👉JD Health faced the challenges of audio-driven video generation in Mandarin, a task complicated by the language’s intricate lip movements and the scarcity of HQ datasets. Impressive results (-> audio ON). Code Models available💙 👉Review 👉Paper arxiv.org/pdf/2409.13268 👉Project jdh-algo.github.io/JoyHallo/ 👉Code github.com/jdh-algo/JoyHallo

⚽ SoccerNet 2024 Results ⚽ 👉SoccerNet is the annual video understanding challenge for football. These challenges aim to advance research across multiple themes in football. The 2024 results are out! 👉Review https://t.ly/DUPgx 👉Paper arxiv.org/pdf/2409.10587 👉Repo github.com/SoccerNet 👉Project www.soccer-net.org/

🧸Motion Instruction Fine-Tuning🧸 👉MotIF is a novel method that fine-tunes pre-trained VLMs to equip the capability to distinguish nuanced robotic motions with different shapes and semantic groundings. A work by MIT, Stanford, and CMU. Source Code announced, coming💙 👉Review https://t.ly/iJ2UY 👉Paper https://arxiv.org/pdf/2409.10683 👉Project https://motif-1k.github.io/ 👉Code coming

🌭Hand-Object interaction Pretraining🌭 👉Berkeley unveils HOP, a novel approach to learn general robot manipulation priors from 3D hand-object interaction trajectories. 👉Review https://t.ly/FLqvJ 👉Paper https://arxiv.org/pdf/2409.08273 👉Project https://hgaurav2k.github.io/hop/

💄Interactive Drag-based Editing💄 👉CSE unveils InstantDrag: novel pipeline designed to enhance editing interactivity and speed, taking only an image and a drag instruction as input. Source Code announced, coming💙 👉Review https://t.ly/hy6SL 👉Paper arxiv.org/pdf/2409.08857 👉Project joonghyuk.com/instantdrag-web/ 👉Code github.com/alex4727/InstantDrag

🫒 Omni Urban Scene Reconstruction 🫒 👉OmniRe is novel holistic approach for efficiently reconstructing HD dynamic urban scenes from on-device logs. It's able to create the simulation of reconstructed scenarios with actors in real-time (~60 Hz). Code released💙 👉Review https://t.ly/SXVPa 👉Paper arxiv.org/pdf/2408.16760 👉Project ziyc.github.io/omnire/ 👉Code github.com/ziyc/drivestudio

🐺 Diffusion Game Engine 🐺 👉#Google unveils GameNGen: the first game engine powered entirely by a neural #AI that enables real-time interaction with a complex environment over long trajectories at HQ. No code announced but I love it 💙 👉Review https://t.ly/_WR5z 👉Paper https://lnkd.in/dZqgiqb9 👉Project https://lnkd.in/dJUd2Fr6

🔥🔥🔥🔥🔥 SOURCE CODE IS OUT !!! 🔥🔥🔥🔥🔥 Thanks Danny for the info 🥇

🦧Sapiens: SOTA ViTs for human🦧 👉META unveils Sapiens, a family of models for human-centric vision tasks: 2D pose estimation, body-part segmentation, depth estimation, and surface normal prediction. Source Code announced, coming💙 👉Review https://t.ly/GKQI0 👉Paper arxiv.org/pdf/2408.12569 👉Project rawalkhirodkar.github.io/sapiens 👉Code github.com/facebookresearch/sapiens

🦓 Zebra Detection & Pose 🦓 👉The first synthetic dataset that can be used for both detection and 2D pose estimation of zebras without applying any bridging strategies. Code, results, models, and the synthetic, training/validation data, including 104K manually labeled images open-sourced💙 👉Review https://t.ly/HTEZZ 👉Paper https://lnkd.in/dQYT-fyq 👉Project https://lnkd.in/dAnNXgG3 👉Code https://lnkd.in/dhvU97xD

🏗️ #Adobe Instant TurboEdit 🏗️ 👉Adobe unveils a novel real-time text-based disentangled real image editing method built upon 4-step SDXL Turbo. SOTA HQ image editing using ultra fast few-step diffusion. No code announced but easy to guess it will be released in commercial tools. 👉Review https://t.ly/Na7-y 👉Paper https://lnkd.in/dVs9RcCK 👉Project https://lnkd.in/dGCqwh9Z 👉Code 😢

🧪 Click-Attention Segmentation 🧪 👉An interesting image patch-based click attention algorithm and an affinity loss inspired by SASFormer. This novel approach aims to decouple positive and negative clicks, guiding positive ones to focus on the target object and negative ones on the background. Code released under Apache💙 👉Review https://t.ly/tG05L 👉Paper https://arxiv.org/pdf/2408.06021 👉Code https://github.com/hahamyt/ClickAttention

👋 Real-time Expressive Hands 👋 👉Zhejiang unveils XHand, a novel expressive hand avatar designed to comprehensively generate hand shape, appearance, and deformations in real-time. Source Code released (Apache 2.0) the Jul. 31st, 2024💙 👉Review https://t.ly/8obbB 👉Project https://lnkd.in/dRtVGe6i 👉Paper https://lnkd.in/daCx2iB7 👉Code https://lnkd.in/dZ9pgzug

🔥🔥 SAM v2 is out! 🔥🔥 👉#Meta announced SAM 2, the novel unified model for real-time promptable segmentation in images and videos. 6x faster, it's the new SOTA by a large margin. Source Code, Dataset, Models & Demo released under permissive licenses💙 👉Review https://t.ly/oovJZ 👉Paper https://t.ly/sCxMY 👉Demo https://sam2.metademolab.com 👉Project ai.meta.com/blog/segment-anything-2/ 👉Models github.com/facebookresearch/segment-anything-2

🪄 Diffusion Models for Transparency 🪄 👉MIT (+ #Google) unveils Alchemist, a novel method to control material attributes of objects like roughness, metallic, albedo & transparency in real images. Amazing work but code not announced🥺 👉Review https://t.ly/U98_G 👉Paper arxiv.org/pdf/2312.02970 👉Project www.prafullsharma.net/alchemist/

🎁 A guide for modern CV 🎁 👉In the last 18 months I received more than 1,100+ applications for research roles. The majority part of the applicants doesn't deeply know a few milestones in CV. Here a short collection of mostly-free resources to spend a bit of good time in the summer. 𝐁𝐨𝐨𝐤𝐬 (recommended): ✅DL with Python https://t.ly/VjaVx ✅Python OOP https://t.ly/pTQRm 𝐎𝐧𝐥𝐢𝐧𝐞 V𝐢𝐝𝐞𝐨 𝐂𝐨𝐮𝐫𝐬𝐞𝐬 (recommended): ✅Berkeley | Modern CV (2023) https://t.ly/AU7S3 𝐋𝐢𝐛𝐫𝐚𝐫𝐢𝐞𝐬: ✅PyTorch https://lnkd.in/dTvJbjAx ✅PyTorchLighting https://lnkd.in/dAruPA6T ✅Albumentations https://albumentations.ai/ 𝐏𝐚𝐩𝐞𝐫𝐬: ✅EfficientNet https://lnkd.in/dTsT44ae ✅ViT https://lnkd.in/dB5yKdaW ✅UNet https://lnkd.in/dnpKVa6T ✅DeepLabV3+ https://lnkd.in/dVvqkmPk ✅YOLOv1: https://lnkd.in/dQ9rs53B ✅YOLOX: https://lnkd.in/d9ZtsF7g 👉More papers and the full list: https://t.ly/WAwAk

👽Keypoint Promptable Re-ID👽 👉KPR is a novel formulation of the ReID problem that explicitly complements the input BBox with a set of semantic keypoints indicating the intended target. Code, dataset and annotations coming soon💙 👉Review https://t.ly/vCXV_ 👉Paper https://arxiv.org/pdf/2407.18112 👉Repo github.com/VlSomers/keypoint_promptable_reidentification

🧱EAFormer: Scene Text-Segm.🧱 👉A novel Edge-Aware Transformers to segment texts more accurately, especially at the edge of
🧱EAFormer: Scene Text-Segm.🧱 👉A novel Edge-Aware Transformers to segment texts more accurately, especially at the edge of texts. FULL re-annotation of COCO_TS and MLT_S! Code coming, data available on 🤗 👉Review https://t.ly/0G2uX 👉Paper https://arxiv.org/pdf/2407.17020 👉Project https://hyangyu.github.io/EAFormer/ 👉Data huggingface.co/datasets/HaiyangYu/TextSegmentation/tree/main

🐢 TAPTRv2: new SOTA for TAP 🐢 👉TAPTRv2: Transformer-based approach built upon TAPTR for solving the Tracking Any Point (TAP) task. TAPTR borrows designs from DETR and formulates each tracking point as a point query, making it possible to leverage well-studied operations in DETR-like algorithms. The Source Code of V1 is available, V2 coming💙 👉Review https://t.ly/H84ae 👉Paper v1 https://lnkd.in/d4vD_6xx 👉Paper v2 https://lnkd.in/dE_TUzar 👉Project https://taptr.github.io/ 👉Code https://lnkd.in/dgfs9Qdy

🏆Who's the REAL SOTA tracker in the world?🏆 👉BofN meta-tracker outperforms, by a large margin, existing SOTA trackers on n
🏆Who's the REAL SOTA tracker in the world?🏆 👉BofN meta-tracker outperforms, by a large margin, existing SOTA trackers on nine standard benchmarks (LaSOT, TrackingNet, GOT-10K, VOT2019, VOT2021, VOT2022, UAV123, OTB100, and WebUAV-3M). Source Code available💙 👉Review https://t.ly/WB9AR 👉Paper https://arxiv.org/pdf/2407.15707 👉Code https://github.com/BasitAlawode/Best_of_N_Trackers