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

Malaysia2 234 Technologies & Applications7 718...

📈 Analytical overview of Telegram channel AI with Papers - Artificial Intelligence & Deep Learning

Channel AI with Papers - Artificial Intelligence & Deep Learning (@ai_deeplearning) in the English language segment is an active participant. Currently, the community unites 17 166 subscribers, ranking 7 718 in the Technologies & Applications category and 2 234 in the Malaysia region.

📊 Audience metrics and dynamics

Since its creation on невідомо, the project has demonstrated rapid growth, gathering an audience of 17 166 subscribers.

According to the latest data from 20 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by -169 over the last 30 days and by 0 over the last 24 hours, overall reach remains high.

Verification status: Not verified
Engagement rate (ER): The average audience engagement rate is 22.86%. Within the first 24 hours after publication, content typically collects N/A% reactions from the total number of subscribers.
Post reach: On average, each post receives 3 926 views. Within the first day, a publication typically gains 0 views.
Reactions and interaction: The audience actively supports content: the average number of reactions per post is 26.
Thematic interests: Content is focused on key topics such as framework, object, dataset, tba, depth.

📝 Description and content policy

The author describes the resource as a platform for expressing subjective opinions:
“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”

Thanks to the high frequency of updates (latest data received on 21 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Technologies & Applications category.

17 166

Subscribers

No data24 hours

-357 days

-16930 days

3 926

Post views

No data24 hours

No data48 hours

22.86%

Engagement rate

No data

Posts per day

Ads index

beta

Posts Archive

17 157

🦢 Track4Gen: Diffusion + Tracking 🦢 👉Track4Gen: spatially aware video generator that combines video diffusion loss with point tracking across frames, providing enhanced spatial supervision on the diffusion features. GenAI with points-based motion control. Stunning results but no code announced😢 👉Review https://t.ly/9ujhc 👉Paper arxiv.org/pdf/2412.06016 👉Project hyeonho99.github.io/track4gen/ 👉Gallery hyeonho99.github.io/track4gen/full.html

17 157

🧤GigaHands: Massive #3D Hands🧤 👉Novel massive #3D bimanual activities dataset: 34 hours of activities, 14k hand motions clips paired with 84k text annotation, 183M+ unique hand images 👉Review https://t.ly/SA0HG 👉Paper www.arxiv.org/pdf/2412.04244 👉Repo github.com/brown-ivl/gigahands 👉Project ivl.cs.brown.edu/research/gigahands.html

17 157

🦘AniGS: Single Pic Animatable Avatar🦘 👉#Alibaba unveils AniGS: given a single human image as input it rebuilds a Hi-Fi 3D avatar in a canonical pose, which can be used for both photorealistic rendering & real-time animation. Source code announced, to be released💙 👉Review https://t.ly/4yfzn 👉Paper arxiv.org/pdf/2412.02684 👉Project lingtengqiu.github.io/2024/AniGS/ 👉Repo github.com/aigc3d/AniGS

17 157

🌈Motion Prompting Video Generation🌈 👉DeepMind unveils ControlNet, novel video generation model conditioned on spatio-temporally sparse or dense motion trajectories. Amazing results, but no code announced 😢 👉Review https://t.ly/VyKbv 👉Paper arxiv.org/pdf/2412.02700 👉Project motion-prompting.github.io

17 157

⚽Universal Soccer Foundation Model⚽ 👉Universal Soccer Video Understanding: SoccerReplay-1988 - the largest multi-modal soccer dataset - and MatchVision - the first vision-lang. foundation models for soccer. Code, dataset & checkpoints to be released💙 👉Review https://t.ly/-X90B 👉Paper https://arxiv.org/pdf/2412.01820 👉Project https://jyrao.github.io/UniSoccer/ 👉Repo https://github.com/jyrao/UniSoccer

17 157

🔥Video Depth without Video Models🔥 👉RollingDepth: turning a single-image latent diffusion model (LDM) into the novel SOTA depth estimator. It works better than dedicated model for depth 🤯 Code under Apache💙 👉Review https://t.ly/R4LqS 👉Paper https://arxiv.org/pdf/2411.19189 👉Project https://rollingdepth.github.io/ 👉Repo https://github.com/prs-eth/rollingdepth

17 157

👺HiFiVFS: Extreme Face Swapping👺 👉HiFiVFS: HQ face swapping videos even in extremely challenging scenarios (occlusion, makeup, lights, extreme poses, etc.). Impressive results, no code announced😢 👉Review https://t.ly/ea8dU 👉Paper https://arxiv.org/pdf/2411.18293 👉Project https://cxcx1996.github.io/HiFiVFS

17 157

👺 HiFiVFS: Extreme Face Swapping 👺 👉#Tencent unveils a novel video face swapping method called HiFiVFS, which can consistently generate HQ face swapping videos even in extremely challenging scenarios (occlusion, makeup, lights, extreme poses, etc.). Impressive results, no code announced😢 👉Review 👉Paper https://arxiv.org/pdf/2411.18293 👉Project https://cxcx1996.github.io/HiFiVFS

17 157

🧶SOTA track-by-propagation🧶 👉SambaMOTR is a novel e2e model (based on Samba) for long-range dependencies and interactions between tracklets to handle complex motion patterns / occlusions. Code in Jan. 25 💙 👉Review https://t.ly/QSQ8L 👉Paper arxiv.org/pdf/2410.01806 👉Project sambamotr.github.io/ 👉Repo https://lnkd.in/dRDX6nk2

17 157

🛟 StableAnimator: ID-aware Humans 🛟 👉StableAnimator: first e2e ID-preserving diffusion for HQ videos without any post-processing. Input: single image + sequence of poses. Insane results! 👉Review https://t.ly/JDtL3 👉Paper https://arxiv.org/pdf/2411.17697 👉Project francis-rings.github.io/StableAnimator/ 👉Code github.com/Francis-Rings/StableAnimator

17 157

🦙 EdgeCape: SOTA Agnostic Pose 🦙 👉EdgeCap: new SOTA in Category-Agnostic Pose Estimation (CAPE): finding keypoints across diverse object categories using only one or a few annotated support images. Source code released💙 👉Review https://t.ly/4TpAs 👉Paper https://arxiv.org/pdf/2411.16665 👉Project https://orhir.github.io/edge_cape/ 👉Code https://github.com/orhir/EdgeCape

17 157

🌎All Languages Matter: LMMs vs. 100 Lang.🌎 👉ALM-Bench aims to assess the next generation of massively multilingual multimodal models in a standardized way, pushing the boundaries of LMMs towards better cultural understanding and inclusivity. Code & Dataset 💙 👉Review https://t.ly/VsoJB 👉Paper https://lnkd.in/ddVVZfi2 👉Project https://lnkd.in/dpssaeRq 👉Code https://lnkd.in/dnbaJJE4 👉Dataset https://lnkd.in/drw-_95v

17 157

🦖Dino-X: Unified Obj-Centric LVM🦖 👉Unified vision model for Open-World Detection, Segmentation, Phrase Grounding, Visual Counting, Pose, Prompt-Free Detection/Recognition, Dense Caption, & more. Demo & API announced 💙 👉Review https://t.ly/CSQon 👉Paper https://lnkd.in/dc44ZM8v 👉Project https://lnkd.in/dehKJVvC 👉Repo https://lnkd.in/df8Kb6iz

17 157

⚔️SAMurai: SAM for Tracking⚔️ 👉UWA unveils SAMURAI, an enhanced adaptation of SAM 2 specifically designed for visual object tracking. New SOTA! Code under Apache 2.0💙 👉Review https://t.ly/yGU0P 👉Paper https://arxiv.org/pdf/2411.11922 👉Repo https://github.com/yangchris11/samurai 👉Project https://yangchris11.github.io/samurai/

17 157

🧰 EchoMimicV2: Semi-body Human 🧰 👉Alipay (ANT Group) unveils EchoMimicV2, the novel SOTA half-body human animation via APD-Harmonization. See clip with audio (ZH/ENG). Code & Demo announced💙 👉Review https://t.ly/enLxJ 👉Paper arxiv.org/pdf/2411.10061 👉Project antgroup.github.io/ai/echomimic_v2/ 👉Repo-v2 github.com/antgroup/echomimic_v2 👉Repo-v1 https://github.com/antgroup/echomimic

17 157

🧶 MagicQuill: super-easy Diffusion Editing 🧶 👉MagicQuill is a novel system designed to support users in smart editing of images. Robust UI/UX (e.g., inserting/erasing objects, colors, etc.) under a multimodal LLM to anticipate user intentions in real time. Code & Demos released 💙 👉Review https://t.ly/hJyLa 👉Paper https://arxiv.org/pdf/2411.09703 👉Project https://magicquill.art/demo/ 👉Repo https://github.com/magic-quill/magicquill 👉Demo https://huggingface.co/spaces/AI4Editing/MagicQuill

17 157

🛥️ Global Tracklet Association MOT 🛥️ 👉A novel universal, model-agnostic method designed to refine and enhance tracklet association for single-camera MOT. Suitable for datasets such as SportsMOT, SoccerNet & similar. Source code released💙 👉Review https://t.ly/gk-yh 👉Paper https://lnkd.in/dvXQVKFw 👉Repo https://lnkd.in/dEJqiyWs

17 157

🔥 4 NanoSeconds inference 🔥 👉LogicTreeNet: convolutional differentiable logic gate net. with logic gate tree kernels: Computer Vision into differentiable LGNs. Up to 6100% smaller than SOTA, inference in 4 NANOsecs! 👉Review https://t.ly/GflOW 👉Paper https://lnkd.in/dAZQr3dW 👉Full clip https://lnkd.in/dvDJ3j-u

17 157

🐔SeedEdit: foundational T2I🐔 👉ByteDance unveils a novel T2I foundational model capable of delivering stable, high-aesthetic image edits which maintain image quality through unlimited rounds of editing instructions. No code announced but a Demo is online💙 👉Review https://t.ly/hPlnN 👉Paper https://arxiv.org/pdf/2411.06686 👉Project team.doubao.com/en/special/seededit 🤗Demo https://huggingface.co/spaces/ByteDance/SeedEdit-APP

17 157

❄️Don’t Look Twice: ViT by RLT❄️ 👉CMU unveils RLT: speeding up the video transformers inspired by run-length encoding for data compression. Speed the training up and reducing the token count by up to 80%! Source Code announced 💙 👉Review https://t.ly/ccSwN 👉Paper https://lnkd.in/d6VXur_q 👉Project https://lnkd.in/d4tXwM5T 👉Repo TBA