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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 17 166 obunachidan iborat bo'lib, Texnologiyalar & Aralashmalar toifasida 7 718-o'rinni va Malayziya mintaqasida 2 234-o'rinni egallagan.
📊 Auditoriya ko‘rsatkichlari va dinamika
невідомо sanasidan buyon loyiha tez o‘sib, 17 166 obunachiga ega bo‘ldi.
20 Iyun, 2026 dagi oxirgi ma’lumotlarga ko‘ra kanal barqaror faollikka ega. Oxirgi 30 kunda obunachilar soni -169 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 22.86% darajada jalb etiladi. Nashrdan keyingi dastlabki 24 soatda kontent odatda umumiy obunachilar sonining N/A% ini tashkil etuvchi reaksiyalarni to‘playdi.
- Post qamrovi: Har bir post o‘rtacha 3 926 marta ko‘riladi; birinchi sutkada odatda 0 ta ko‘rish yig‘iladi.
- Reaksiyalar va o‘zaro ta’sir: Auditoriya faol: har bir postga o‘rtacha 26 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 21 Iyun, 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.
17 166
Obunachilar
Ma'lumot yo'q24 soatlar
-357 kunlar
-16930 kunlar
Postlar arxiv
🦢 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
🧤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
🦘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
🌈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
⚽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
🔥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
👺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
👺 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
🧶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
🛟 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
🦙 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
🌎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
🦖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
⚔️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/
🧰 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
🧶 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
🛥️ 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
🔥 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
🐔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
❄️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
