现已上线！2025 年 Telegram 研究 — 年度关键洞察 
AI with Papers - Artificial Intelligence & Deep Learning
前往频道在 Telegram
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
显示更多📈 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 17 154 名订阅者，在 技术与应用 类别中位列第 7 726，并在 马来西亚 地区排名第 2 240 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 17 154 名订阅者。
根据 21 六月, 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 -166，过去 24 小时变化为 -6，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 23.63%。内容发布后 24 小时内通常能获得 6.86% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 4 057 次浏览，首日通常累积 1 177 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 26。
- 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 22 六月, 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。
17 154
订阅者
-624 小时
-277 天
-16630 天
帖子存档
🔥🔥🔥🔥🔥 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 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 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
🎭 TRG: new SOTA in 6DoF Head 🎭
👉ECE (Korea) unveils TRG, a novel landmark-based method for estimating a 6DoF head pose which stands out for its explicit bidirectional interaction structure. Experiments on ARKitFace & BIWI confirm it's the new SOTA. Source Code & Models to be released💙
👉Review https://t.ly/lOIRA
👉Paper https://lnkd.in/dCWEwNyF
👉Code https://lnkd.in/dzRrwKBD
🧿 Shape of Motion for 4D 🧿
👉 Google (+Berkeley) unveils a novel method capable of reconstructing generic dynamic scenes, featuring explicit, full-sequence-long 3D motion, from casually captured monocular videos. Impressive tracking capabilities. Source Code released 💙
👉Review https://t.ly/d9RsA
👉Project https://shape-of-motion.github.io/
👉Paper arxiv.org/pdf/2407.13764
👉Code github.com/vye16/shape-of-motion/
Hi folks,
I need you help 🙏
👉 Could you help me understanding what do you think about the lasting of the hiring process for #artificialintelligence roles? Any comment here will be appreciated :)
Vote here: https://t.ly/UMRXH
Thanks <3
📈Gradient Boosting Reinforcement Learning📈
👉#Nvidia unveils GBRL, a framework that extends the advantages of Gradient Boosting Trees to the RL domain. GBRL adapts the power of Gradient Boosting Trees to the unique challenges of RL environments, including non-stationarity and absence of predefined targets. Code released💙
👉Review https://t.ly/zv9pl
👉Paper https://arxiv.org/pdf/2407.08250
👉Code https://github.com/NVlabs/gbrl
💌 KineTy: Typography Diffusion 💌
👉GIST introduces a novel realistic kinetic typography generation driven by text description. Guided video diffusion models to achieve visually-pleasing text appearances. Repo to be released under Attribution-NC 4.0💙
👉Review https://t.ly/2FWo9
👉Paper arxiv.org/pdf/2407.10476
👉Project seonmip.github.io/kinety/
👉Repo github.com/SeonmiP/KineTy/tree/main
💌 KineTy: Typography Diffusion 💌
👉GIST introduces a novel realistic kinetic typography generation driven by text description. Guided video diffusion models to achieve visually-pleasing text appearances. Repo to be released under Attribution-NC 4.0💙
👉Review https://t.ly/2FWo9
👉Paper arxiv.org/pdf/2407.10476
👉Project seonmip.github.io/kinety/
👉Repo github.com/SeonmiP/KineTy/tree/main
🥥 OmniNOCS: largest 3D NOCS 🥥
👉OmniNOCS by #Google (+Georgia) is a unified NOCS (Normalized Object Coordinate Space) dataset that contains data across different domains with 90+ object classes. The largest NOCS dataset to date. Data & Code available under Apache 2.0💙
👉Review https://t.ly/xPgBn
👉Paper arxiv.org/pdf/2407.08711
👉Project https://omninocs.github.io/
👉Data github.com/google-deepmind/omninocs
