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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

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📈 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 17 261 名订阅者,在 技术与应用 类别中位列第 7 500,并在 马来西亚 地区排名第 2 124 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 17 261 名订阅者。

根据 24 十月, 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 258,过去 24 小时变化为 -2,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 16.76%。内容发布后 24 小时内通常能获得 7.11% 的反应,占订阅者总量。
  • 帖子覆盖: 每篇帖子平均可获得 2 893 次浏览,首日通常累积 1 227 次浏览。
  • 互动与反馈: 受众积极参与,单帖平均反应数为 16。
  • 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 25 十月, 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。

17 261
订阅者
-224 小时
+27 天
+25830 天
帖子存档
🌏 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