Загрузка видео...

Не удалось загрузить видео

Возникла проблема при загрузке этого видео. Это может быть связано с временными проблемами сети или видео может быть недоступно.

На главную

Mapbox has a brand new 3D map style, still in beta! But it didn’t have a hackable live demo, so at Skydio we created one 😎 , try it out here: The updates include: - Hundreds of new 3D models for famous landmarks - New symbolic design that works... show more

Alberto

5,358 subscribers

43,945 просмотров • 3 лет назад •via X (Twitter)

Anya Rossi• Live Now

Private livecam show

Комментарии: 6

Фото профиля Tom Osman 🐦‍⬛

Tom Osman 🐦‍⬛3 лет назад

@Scobleizer Anyway we can bring a custom Mapbox setup into our @glideapps @dvdsgl?

Фото профиля RedDeer.Games

RedDeer.Games1 год назад

🚨 New HIT on Nintendo! 🚨 🎮 My Cozy Room – the ultimate sandbox game to unleash your creativity! 🛋️Design dream spaces with 500+ furniture items & 30+ styles. 👉 Play now: #Nintendo #Indiegames #RedDeerGames #MyCozyRoom

Фото профиля Adrian Babilinski

Adrian Babilinski3 лет назад

Very impressive! Looks better than Google Maps

Фото профиля Zander

Zander3 лет назад

Looks similar to Apple Maps

Фото профиля Chris Matthieu

Chris Matthieu3 лет назад

Nice!

Фото профиля gturbaines🔻𓂆

gturbaines🔻𓂆3 лет назад

@digitalurban

Похожие видео

This is what a hand drawn SDF shadow map looks like on a 3D vtuber model! A lot of games that have an anime art style use this technique🩷 I wanted to try making my own for our 3D customizable vtuber avatar✨It will be included for free in the first update!

Pastell & Palette🤍 3D Customizable Model!

24,346 просмотров • 10 месяцев назад

Large-scale Gaussian splats have reached a new level of realism. This is a well-known temple in Bangkok, reconstructed as a high-fidelity 3D environment from 360 captures. At this level, the boundary between video and 3D starts to disappear. But what you’re looking at is not a video. It’s a dense spatial representation of a real place, where geometry, texture, and structure are preserved and made machine-readable. This kind of 3D data can power Visual AI, Robotics navigation, VPS localization, XR experiences, world models, and next-generation spatial computing systems. Built with Over the Reality.

Large-scale Gaussian splats have reached a new level of realism. This is a well-known temple in Bangkok, reconstructed as a high-fidelity 3D environment from 360 captures. At this level, the boundary between video and 3D starts to disappear. But what you’re looking at is not a video. It’s a dense spatial representation of a real place, where geometry, texture, and structure are preserved and made machine-readable. This kind of 3D data can power Visual AI, Robotics navigation, VPS localization, XR experiences, world models, and next-generation spatial computing systems. Built with Over the Reality.

Over the Reality 🌐

347,394 просмотров • 4 месяцев назад

3D-LLM: Injecting the 3D World into Large Language Models paper page: Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this work, we propose to inject the 3D world into large language models and introduce a whole new family of 3D-LLMs. Specifically, 3D-LLMs can take 3D point clouds and their features as input and perform a diverse set of 3D-related tasks, including captioning, dense captioning, 3D question answering, task decomposition, 3D grounding, 3D-assisted dialog, navigation, and so on. Using three types of prompting mechanisms that we design, we are able to collect over 300k 3D-language data covering these tasks. To efficiently train 3D-LLMs, we first utilize a 3D feature extractor that obtains 3D features from rendered multi- view images. Then, we use 2D VLMs as our backbones to train our 3D-LLMs. By introducing a 3D localization mechanism, 3D-LLMs can better capture 3D spatial information. Experiments on ScanQA show that our model outperforms state-of-the-art baselines by a large margin (e.g., the BLEU-1 score surpasses state-of-the-art score by 9%). Furthermore, experiments on our held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that our model outperforms 2D VLMs. Qualitative examples also show that our model could perform more tasks beyond the scope of existing LLMs and VLMs.

3D-LLM: Injecting the 3D World into Large Language Models paper page: Large language models (LLMs) and Vision-Language Models (VLMs) have been proven to excel at multiple tasks, such as commonsense reasoning. Powerful as these models can be, they are not grounded in the 3D physical world, which involves richer concepts such as spatial relationships, affordances, physics, layout, and so on. In this work, we propose to inject the 3D world into large language models and introduce a whole new family of 3D-LLMs. Specifically, 3D-LLMs can take 3D point clouds and their features as input and perform a diverse set of 3D-related tasks, including captioning, dense captioning, 3D question answering, task decomposition, 3D grounding, 3D-assisted dialog, navigation, and so on. Using three types of prompting mechanisms that we design, we are able to collect over 300k 3D-language data covering these tasks. To efficiently train 3D-LLMs, we first utilize a 3D feature extractor that obtains 3D features from rendered multi- view images. Then, we use 2D VLMs as our backbones to train our 3D-LLMs. By introducing a 3D localization mechanism, 3D-LLMs can better capture 3D spatial information. Experiments on ScanQA show that our model outperforms state-of-the-art baselines by a large margin (e.g., the BLEU-1 score surpasses state-of-the-art score by 9%). Furthermore, experiments on our held-in datasets for 3D captioning, task composition, and 3D-assisted dialogue show that our model outperforms 2D VLMs. Qualitative examples also show that our model could perform more tasks beyond the scope of existing LLMs and VLMs.

AK

249,798 просмотров • 3 лет назад

Apple Maps 3d is insanely impressive now (see video below) Google on the other hand decided to build an insanely clunky solution to display 3d maps to avoid using mobile GPUs: A Google server streams (!) a live video of its 3d rendered map to you, the result is a disastrous: a super laggy and clunky 3d view full of video compression artefacts with a response time of 2-3 seconds for every movement And I know WHY they built that, someone felt it was not inclusive to only have 3d maps that are high performing on iOS because Apple's GPUs are insanely fast and can deal with it (as you can see below in Apple Maps) but they wanted to support inferior phones, I get it But then they also decided to worsen the experience for iOS users who could easily run 3d natively on its GPU It's just an insane product decision, there's no way to cut it: they could have super smooth 3d like Apple Maps but neutered it with a clunky live stream Even more insane because Google does have native 3d on iOS in a completely different app that nobody uses: Google Earth Is 3d important? Not rly for nav no but it shows again something about Google's engineering decisions, like the redesign of the Google OAuth Login screen that made zero sense Nobody is speaking up against bad ideas in Google meetings, everyone's too scared of HR maybe, it's the opposite of a meritocracy and it's just super visible from using Google products right now

Apple Maps 3d is insanely impressive now (see video below) Google on the other hand decided to build an insanely clunky solution to display 3d maps to avoid using mobile GPUs: A Google server streams (!) a live video of its 3d rendered map to you, the result is a disastrous: a super laggy and clunky 3d view full of video compression artefacts with a response time of 2-3 seconds for every movement And I know WHY they built that, someone felt it was not inclusive to only have 3d maps that are high performing on iOS because Apple's GPUs are insanely fast and can deal with it (as you can see below in Apple Maps) but they wanted to support inferior phones, I get it But then they also decided to worsen the experience for iOS users who could easily run 3d natively on its GPU It's just an insane product decision, there's no way to cut it: they could have super smooth 3d like Apple Maps but neutered it with a clunky live stream Even more insane because Google does have native 3d on iOS in a completely different app that nobody uses: Google Earth Is 3d important? Not rly for nav no but it shows again something about Google's engineering decisions, like the redesign of the Google OAuth Login screen that made zero sense Nobody is speaking up against bad ideas in Google meetings, everyone's too scared of HR maybe, it's the opposite of a meritocracy and it's just super visible from using Google products right now

@levelsio

1,489,214 просмотров • 2 лет назад

WOW. 😳 Apple just quietly won the 3D maps war at WWDC. Gaussian Splatting is coming to Apple Maps Flyover this fall. Apple Maps Flyover covers 300+ cities. Until yesterday, every single one was built on standard drone photogrammetry. The technology captures photos from the air and reconstructs 3D geometry from them. Gaussian Splatting does not reconstruct geometry. It represents the scene as millions of tiny 3D ellipsoids, each one carrying its own color and opacity information based on how light actually behaves in that location. The output is not a mesh model. It is a field of light. When you move through it, it does not crumble at the edges. The detail holds because it was never geometry to begin with. Apple has been hiring for this for years. Their SHARP model, published in research last year, generates photorealistic 3D scenes from a single image in under a second. Google has more sensor data than anyone. More Street View cars, more satellites, more capture history. On navigation accuracy and geodata depth, Google Maps is still ahead by most measures. But fidelity in 3D city rendering is a different competition, and Apple just set a bar in that. Most people will experience this in the fall without knowing the name of the technology. They will open Flyover, look at a city they know, and notice it looks different. Real, not rendered. That is the moment Gaussian Splatting stops being a research term and becomes something a billion people use. Bookmark this. It will look prescient by October.

WOW. 😳 Apple just quietly won the 3D maps war at WWDC. Gaussian Splatting is coming to Apple Maps Flyover this fall. Apple Maps Flyover covers 300+ cities. Until yesterday, every single one was built on standard drone photogrammetry. The technology captures photos from the air and reconstructs 3D geometry from them. Gaussian Splatting does not reconstruct geometry. It represents the scene as millions of tiny 3D ellipsoids, each one carrying its own color and opacity information based on how light actually behaves in that location. The output is not a mesh model. It is a field of light. When you move through it, it does not crumble at the edges. The detail holds because it was never geometry to begin with. Apple has been hiring for this for years. Their SHARP model, published in research last year, generates photorealistic 3D scenes from a single image in under a second. Google has more sensor data than anyone. More Street View cars, more satellites, more capture history. On navigation accuracy and geodata depth, Google Maps is still ahead by most measures. But fidelity in 3D city rendering is a different competition, and Apple just set a bar in that. Most people will experience this in the fall without knowing the name of the technology. They will open Flyover, look at a city they know, and notice it looks different. Real, not rendered. That is the moment Gaussian Splatting stops being a research term and becomes something a billion people use. Bookmark this. It will look prescient by October.

Shruti

19,832 просмотров • 3 месяцев назад

Why do we still buy stadium tickets without ever seeing what the view from the seat actually looks like? ☠️ So I prototyped an idea. A 3D seat view experience for a football stadium built with Fable 5 + Three.js, where you can preview exactly what you'll see from your seat before buying. The entire 3D experience was working after the first prompt, and the whole prototype came together in just five prompts. This is the kind of 3D experience I'd love to see more of, tbh. Feels so good. Right now, buying a ticket gives you almost no sense of what the experience will actually feel like. We're still relying on static seat maps, charts, and boring UI layouts, when interactive 3D experiences could make that decision so much easier. If you think, 3D development has the potential to create genuinely useful experiences. This feels like the direction we should be heading. 3D is the future. I can already imagine this for cinemas, cricket stadiums, Wimbledon, concerts, and so many other venues. I'm planning to take this further. What should I build next? More stadium features, or should I try another venue? Let me know :D Code: Live:

Why do we still buy stadium tickets without ever seeing what the view from the seat actually looks like? ☠️ So I prototyped an idea. A 3D seat view experience for a football stadium built with Fable 5 + Three.js, where you can preview exactly what you'll see from your seat before buying. The entire 3D experience was working after the first prompt, and the whole prototype came together in just five prompts. This is the kind of 3D experience I'd love to see more of, tbh. Feels so good. Right now, buying a ticket gives you almost no sense of what the experience will actually feel like. We're still relying on static seat maps, charts, and boring UI layouts, when interactive 3D experiences could make that decision so much easier. If you think, 3D development has the potential to create genuinely useful experiences. This feels like the direction we should be heading. 3D is the future. I can already imagine this for cinemas, cricket stadiums, Wimbledon, concerts, and so many other venues. I'm planning to take this further. What should I build next? More stadium features, or should I try another venue? Let me know :D Code: Live:

The Bugged Dev

1,807,787 просмотров • 2 месяцев назад

Running some more tests with Adobe’s new 3D model viewer, Gaussian Splatting generator, and AI image generator, 'Substance 3D Viewer.' It’s still in beta, but it’s already pretty awesome and very easy to use! 🔥 Check out what I was able to create. The models in this video were made with Tripo AI using text-to-3D, and the animations were brought to life using Hailuo and Luma Dream. This tech just keeps getting more useful! #AIArt #3DModeling #Substance3DViewer

Running some more tests with Adobe’s new 3D model viewer, Gaussian Splatting generator, and AI image generator, 'Substance 3D Viewer.' It’s still in beta, but it’s already pretty awesome and very easy to use! 🔥 Check out what I was able to create. The models in this video were made with Tripo AI using text-to-3D, and the animations were brought to life using Hailuo and Luma Dream. This tech just keeps getting more useful! #AIArt #3DModeling #Substance3DViewer

Martin Nebelong

87,635 просмотров • 1 год назад

This was way too easy... I created a cute 3D character in minutes instead of hours using this combo: Unbound + Tripo I’m not a 3D artist, but this made the whole process feel simple, playful, and actually accessible. Unbound helped me shape the character idea, then Tripo turned it into a 3D model without the usual complicated workflow If you are a 3D artist or you are just starting, try Unbound. It’s free, open for everyone to experiment with, and a fun way to create characters, creatures, and 3D models without feeling overwhelmed I had so much fun using it today, and I think many visual creators are going to love it. Link in the first comment 👇🏻

This was way too easy... I created a cute 3D character in minutes instead of hours using this combo: Unbound + Tripo I’m not a 3D artist, but this made the whole process feel simple, playful, and actually accessible. Unbound helped me shape the character idea, then Tripo turned it into a 3D model without the usual complicated workflow If you are a 3D artist or you are just starting, try Unbound. It’s free, open for everyone to experiment with, and a fun way to create characters, creatures, and 3D models without feeling overwhelmed I had so much fun using it today, and I think many visual creators are going to love it. Link in the first comment 👇🏻

Amira Zairi

186,621 просмотров • 5 месяцев назад

🚀✨ A Year of 3D Development! AI Solutions for Fashion ✨🚀 Reflecting on an incredible year of intensive 3D development – a journey where innovation met determination. Back in the day, we navigated the challenges without the aid of AI solutions to craft cutting-edge fashion 3D assets. But guess what? Fast forward to now, and the game has completely changed! 🌐👗 Today, with the power of AI solutions at our fingertips, the process of creating fashion assets has skyrocketed in efficiency, clocking in at a jaw-dropping 10 times faster! 🚀💨 The marriage of creativity and artificial intelligence has truly revolutionized our approach, bringing forth a new era in 3D design. As we celebrate this milestone, we can't help but look ahead to the future. Just like the highly anticipated release of GTA 6 in 2025, Avatly is gearing up to set the pace for what's next. ⚡️🎮 Our commitment to innovation knows no bounds, and we're determined to outpace expectations, ensuring that Avatly stands as a trailblazer in the evolving landscape of 3D development. Join us on this thrilling journey where technology and creativity converge, propelling us into a future where the possibilities are as endless as our imagination! === BUY AVA TOKEN === 💎Bitmart: 💎Pancakeswap:

🚀✨ A Year of 3D Development! AI Solutions for Fashion ✨🚀 Reflecting on an incredible year of intensive 3D development – a journey where innovation met determination. Back in the day, we navigated the challenges without the aid of AI solutions to craft cutting-edge fashion 3D assets. But guess what? Fast forward to now, and the game has completely changed! 🌐👗 Today, with the power of AI solutions at our fingertips, the process of creating fashion assets has skyrocketed in efficiency, clocking in at a jaw-dropping 10 times faster! 🚀💨 The marriage of creativity and artificial intelligence has truly revolutionized our approach, bringing forth a new era in 3D design. As we celebrate this milestone, we can't help but look ahead to the future. Just like the highly anticipated release of GTA 6 in 2025, Avatly is gearing up to set the pace for what's next. ⚡️🎮 Our commitment to innovation knows no bounds, and we're determined to outpace expectations, ensuring that Avatly stands as a trailblazer in the evolving landscape of 3D development. Join us on this thrilling journey where technology and creativity converge, propelling us into a future where the possibilities are as endless as our imagination! === BUY AVA TOKEN === 💎Bitmart: 💎Pancakeswap:

Avatly 💎

15,428 просмотров • 2 лет назад

3d visual positioning experiment -- look at the alignment between the 3d mesh and the live camera view. Truly feels magical -- like x-ray vision. Workflow: 1. Scanned a street in 15 mins w/ xgrids 2. Localized against that scan at night, in real-time, while sitting in a car The xgrids scanner (w/ rgb + lidar) is perfect to build maps for humans (3d gaussian splats). Then multiset ai makes it easy to build machine-readable maps for AR and robotics to figure out exactly where they are in 3d space with cm-level accuracy.

3d visual positioning experiment -- look at the alignment between the 3d mesh and the live camera view. Truly feels magical -- like x-ray vision. Workflow: 1. Scanned a street in 15 mins w/ xgrids 2. Localized against that scan at night, in real-time, while sitting in a car The xgrids scanner (w/ rgb + lidar) is perfect to build maps for humans (3d gaussian splats). Then multiset ai makes it easy to build machine-readable maps for AR and robotics to figure out exactly where they are in 3d space with cm-level accuracy.

Bilawal Sidhu

27,485 просмотров • 10 месяцев назад

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Here's a look behind the scenes of how I used a 3d model, generated from an image, as a "driver" for ai animation. In the near future we'll see more 3d tools that support these types of workflows, with much more emphasis on enhancing user input instead of just letting the ai do everything. I used the 3d model to generate keyframes that I then animated in Luma Dream. By using a 3d model with a diffusion "layer" done with Krea, I got quite high quality frames with a relatively high consistency as well since the AI didn't have to "hallucinate" that much. I upscaled and detailed the frames using Magnific. Using semi-detailed 3d models as drivers for gen ai is very powerful, and it allows us to use models that are sculpted in a more free-flowing type of workflow that doesn't rely so much on high surface detailing or very time-consuming finish, but instead relies more on gestural 3d sculpting. #art #ai

Martin Nebelong

48,280 просмотров • 2 лет назад

Here is DLSS5 working on an animation I made in Unreal. It uses the existing geometry, animation, textures and lighting to render. It doesn't make stuff up out of thin air. There is zero generative AI. This is the exact use of AI that people have wanted. As a tool where artists maintain full art direction. Neural rendering makes creating amazing art with real 3D models easier and more accessible. All 3D artists should be excited. Here is another explanation by Daniel Vávra ⚔ Is this a 3D model? I encourage you to create a 3D model or animation sometime and try it out for yourself, it can be fun creating something!

Here is DLSS5 working on an animation I made in Unreal. It uses the existing geometry, animation, textures and lighting to render. It doesn't make stuff up out of thin air. There is zero generative AI. This is the exact use of AI that people have wanted. As a tool where artists maintain full art direction. Neural rendering makes creating amazing art with real 3D models easier and more accessible. All 3D artists should be excited. Here is another explanation by Daniel Vávra ⚔ Is this a 3D model? I encourage you to create a 3D model or animation sometime and try it out for yourself, it can be fun creating something!

Unreal Sensei

125,554 просмотров • 1 месяц назад

Added 3d buildings now to Together with [ 💰 Income mode ] it looks pretty cool and you can see the average income per neighborhood of hundreds of cities around the world that I just added! Just zoom in and hold CTRL and drag your mouse, or on mobile drag with two fingers to go 3d! Nice if you are figuring out where to stay in a city, or even where to live maybe Here's NYC's median income map:

Added 3d buildings now to Together with [ 💰 Income mode ] it looks pretty cool and you can see the average income per neighborhood of hundreds of cities around the world that I just added! Just zoom in and hold CTRL and drag your mouse, or on mobile drag with two fingers to go 3d! Nice if you are figuring out where to stay in a city, or even where to live maybe Here's NYC's median income map:

@levelsio

249,112 просмотров • 1 месяц назад

We are developing a new design paradigm that enables seamless integration of 2D and 3D on the same canvas in real time. No need for plugins or cumbersome workflows. It's all connected in a single place. All systems (frames, layouts, booleans, vectors, effects, etc.) work in sync across 2D and 3D, non-destructively. This is the starting point of a fully multi-dimensional design process. At some point in the near future, people won't need to refer to '3d design' as a separate part of the process, because it will be all part of the same system. The following is a demo of this in the works within Hana (a design canvas). We will ship this latest development in about a week.

We are developing a new design paradigm that enables seamless integration of 2D and 3D on the same canvas in real time. No need for plugins or cumbersome workflows. It's all connected in a single place. All systems (frames, layouts, booleans, vectors, effects, etc.) work in sync across 2D and 3D, non-destructively. This is the starting point of a fully multi-dimensional design process. At some point in the near future, people won't need to refer to '3d design' as a separate part of the process, because it will be all part of the same system. The following is a demo of this in the works within Hana (a design canvas). We will ship this latest development in about a week.

Spline

56,203 просмотров • 8 месяцев назад

Volumetric, animated 3D noise shader block in Unity. Where each frame is 2D space, and the 3rd dimension is time. So that, measurement of change within a slice is 'space', and measurement of change across slices is 'time'. As a 3D block, you see the noise animate into the 3rd dimension, but when looking at only a single slice, it appears to evolve in place. Likewise, for 4D... If: this were 3D noise, then: the 4th dimension would be whatever processing/frames/states of 3D data.

Volumetric, animated 3D noise shader block in Unity. Where each frame is 2D space, and the 3rd dimension is time. So that, measurement of change within a slice is 'space', and measurement of change across slices is 'time'. As a 3D block, you see the noise animate into the 3rd dimension, but when looking at only a single slice, it appears to evolve in place. Likewise, for 4D... If: this were 3D noise, then: the 4th dimension would be whatever processing/frames/states of 3D data.

Mirza Beig

126,907 просмотров • 9 месяцев назад

We also worked with the folks at JigSpace to view one of our scans in 3D (this is a Luer lock–check out the thread for more on how these ingenious medical connectors work).

We also worked with the folks at JigSpace to view one of our scans in 3D (this is a Luer lock–check out the thread for more on how these ingenious medical connectors work).

Jon Bruner

44,644 просмотров • 2 лет назад

Scaling 3D scene data is a long-standing challenge in scene understanding, spatial reasoning, and robotics. Since scanning, reconstruction, and labeling are so labor-intensive, data scarcity has remained a major bottleneck. 🛑 To solve this, we propose SceneVerse++: Lifting Unlabeled Internet-level Data for 3D Scene Understanding (CVPR 2026). By reconstructing internet videos and annotating 3D scenes automatically, we’ve created a massive real-world dataset for end-to-end understanding. 🌐📐 SceneVerse++ makes it easy to scale "in-the-wild" 3D scenes toward more capable spatial reasoning systems. This significantly promotes progress in 3D VQA, visual navigation, and broader tasks in Embodied AI and Robotics. 🤖🦾 We are fully open-sourced! Check out the paper, code, and data here: 🌐 Project: 📄 Paper: 📊 Dataset: Code:

Scaling 3D scene data is a long-standing challenge in scene understanding, spatial reasoning, and robotics. Since scanning, reconstruction, and labeling are so labor-intensive, data scarcity has remained a major bottleneck. 🛑 To solve this, we propose SceneVerse++: Lifting Unlabeled Internet-level Data for 3D Scene Understanding (CVPR 2026). By reconstructing internet videos and annotating 3D scenes automatically, we’ve created a massive real-world dataset for end-to-end understanding. 🌐📐 SceneVerse++ makes it easy to scale "in-the-wild" 3D scenes toward more capable spatial reasoning systems. This significantly promotes progress in 3D VQA, visual navigation, and broader tasks in Embodied AI and Robotics. 🤖🦾 We are fully open-sourced! Check out the paper, code, and data here: 🌐 Project: 📄 Paper: 📊 Dataset: Code:

Siyuan Huang

12,842 просмотров • 5 месяцев назад