Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

Announcing the Video Editor in Spatial Media Toolkit. Effortlessly create spatial videos or photo slideshows with music, all privately on-device. Seamlessly integrates with our powerful 2D-to-3D conversion for stunning spatial storytelling.

theryangordon's profile picture

Ryan Gordon

3,357 subscribers

12,353 Aufrufe • vor 1 Jahr •via X (Twitter)

LIVE

Anya Rossi• Live Now

Private livecam show

0 Kommentare

Keine Kommentare verfügbar

Kommentare vom Original-Post werden hier angezeigt

Ähnliche Videos

Video to Spatial conversion coming soon to Spatial Media Tookit. Here's 1080p 10sec Sora mammoth video, all converted on device. The effect is unreal. #visonpro #spatialvideo #sora You can already convert Photos to Spatial right now! download here:
0:37

Video to Spatial conversion coming soon to Spatial Media Tookit. Here's 1080p 10sec Sora mammoth video, all converted on device. The effect is unreal. #visonpro #spatialvideo #sora You can already convert Photos to Spatial right now! download here:

Ryan Gordon

12,131 Aufrufe • vor 2 Jahren

New research with Tsinghua University: Spatial-TTT. A framework for streaming visual-based spatial intelligence with test-time training (TTT). Spatial-TTT adapts fast weights to capture and organize spatial evidence from long video streams, enabling models to build structured 3D spatial memory over time. Highlights: 🔹Efficient streaming memory. Fast weights act as compact spatial memory with sublinear memory growth over 7000+ frames and more than 40% lower compute. 🔹Spatial-predictive mechanism. TTT layers with 3D spatiotemporal convolution capture geometric correspondence and temporal continuity. 🔹SOTA results on long-horizon video spatial understanding (VSI-Bench). The paper ranked #1 on Hugging Face Daily Papers on March 13. Project page: GitHub: Paper: Model & Data:
0:47

New research with Tsinghua University: Spatial-TTT. A framework for streaming visual-based spatial intelligence with test-time training (TTT). Spatial-TTT adapts fast weights to capture and organize spatial evidence from long video streams, enabling models to build structured 3D spatial memory over time. Highlights: 🔹Efficient streaming memory. Fast weights act as compact spatial memory with sublinear memory growth over 7000+ frames and more than 40% lower compute. 🔹Spatial-predictive mechanism. TTT layers with 3D spatiotemporal convolution capture geometric correspondence and temporal continuity. 🔹SOTA results on long-horizon video spatial understanding (VSI-Bench). The paper ranked #1 on Hugging Face Daily Papers on March 13. Project page: GitHub: Paper: Model & Data:

Tencent Hy

20,792 Aufrufe • vor 4 Monaten

I asked Gemini 3 Pro to create a 3D LEGO editor. In one shot it nailed the UI, complex spatial logic, and all the functionality. We’re entering a new era.
0:26

I asked Gemini 3 Pro to create a 3D LEGO editor. In one shot it nailed the UI, complex spatial logic, and all the functionality. We’re entering a new era.

Pietro Schirano

1,673,367 Aufrufe • vor 8 Monaten

I totally didn’t realize that Preview on MacOS also implements the new Spatial Preview with Vision Pro! Really freaking awesome to see ALL of Apple’s operating systems incorporating such huge implementations for Spatial Computing
0:58

I totally didn’t realize that Preview on MacOS also implements the new Spatial Preview with Vision Pro! Really freaking awesome to see ALL of Apple’s operating systems incorporating such huge implementations for Spatial Computing

Brad Lynch

24,915 Aufrufe • vor 1 Monat

One of my new favorite apps on Apple Vision Pro is Story: Spatial Storytelling! It lets you create immersive experiences with text, images, videos, 3D models, keyframing, and more. You can also explore incredible creations from others. Definitely worth checking out!
0:27

One of my new favorite apps on Apple Vision Pro is Story: Spatial Storytelling! It lets you create immersive experiences with text, images, videos, 3D models, keyframing, and more. You can also explore incredible creations from others. Definitely worth checking out!

Justin Ryan ᯅ

20,495 Aufrufe • vor 1 Jahr

Today’s hobby project: Prototyped a real-time room scanning system with live sharing to XR devices. Explore scanned spaces in 3D on XR (not flat 2D screens) and share them with remote users for spatial remote collaboration. #metaquest #augmentedreality
3:07

Today’s hobby project: Prototyped a real-time room scanning system with live sharing to XR devices. Explore scanned spaces in 3D on XR (not flat 2D screens) and share them with remote users for spatial remote collaboration. #metaquest #augmentedreality

Takashi Yoshinaga

125,679 Aufrufe • vor 7 Monaten

POWER TO THE PEOPLE (Live at the One To One Concert - Afternoon and Evening Shows) Listen now in Spatial Audio with Dolby Atmos on Apple Music
0:29

POWER TO THE PEOPLE (Live at the One To One Concert - Afternoon and Evening Shows) Listen now in Spatial Audio with Dolby Atmos on Apple Music

Yoko Ono

12,539 Aufrufe • vor 9 Monaten

📹 Behind the scenes with our project manager Giuseppe Sarri on the last tests performed on #ESAJuice before it left for Centre spatial guyanais Full video 👉
1:00

📹 Behind the scenes with our project manager Giuseppe Sarri on the last tests performed on #ESAJuice before it left for Centre spatial guyanais Full video 👉

ESA's Juice mission

55,176 Aufrufe • vor 3 Jahren

Excited to share our latest work on 🎧spatial audio-driven human motion generation. We aim to tackle a largely underexplored yet important problem of enabling virtual humans to move naturally in response to spatial audio—capturing not just what is heard, but also where the sound is coming from. To this end, we introduce the Spatial Audio-Driven Human Motion (SAM) dataset—the first comprehensive dataset featuring paired high-quality human motion and spatial audio recordings. For benchmarking, we develop a generative framework for human MOtion generation driven by SPAtial audio, termed MOSPA, which learns to synthesize realistic and diverse human motions conditioned on spatial audio input. We hope this research could provide a foundation for future research in spatial perception, virtual characters, and embodied AI. The dataset and model will be open-sourced soon. A big thank you to our intern, Shuyang Xu, for the wonderful collaboration! Congratulations, Shuyang! Project page: Paper: Video: #Animation #CG #CV #AIGC #DL #Deeplearning #Motion #Graphics #AI #GenerativeAI
3:58

Excited to share our latest work on 🎧spatial audio-driven human motion generation. We aim to tackle a largely underexplored yet important problem of enabling virtual humans to move naturally in response to spatial audio—capturing not just what is heard, but also where the sound is coming from. To this end, we introduce the Spatial Audio-Driven Human Motion (SAM) dataset—the first comprehensive dataset featuring paired high-quality human motion and spatial audio recordings. For benchmarking, we develop a generative framework for human MOtion generation driven by SPAtial audio, termed MOSPA, which learns to synthesize realistic and diverse human motions conditioned on spatial audio input. We hope this research could provide a foundation for future research in spatial perception, virtual characters, and embodied AI. The dataset and model will be open-sourced soon. A big thank you to our intern, Shuyang Xu, for the wonderful collaboration! Congratulations, Shuyang! Project page: Paper: Video: #Animation #CG #CV #AIGC #DL #Deeplearning #Motion #Graphics #AI #GenerativeAI

Zhiyang (Frank) Dou

14,610 Aufrufe • vor 1 Jahr

Just experienced the future of shopping with Alibaba’s Taobao on Vision Pro. High-res 3D models and spatial videos make it incredibly immersive. E-commerce is about to change forever.
0:54

Just experienced the future of shopping with Alibaba’s Taobao on Vision Pro. High-res 3D models and spatial videos make it incredibly immersive. E-commerce is about to change forever.

Justin Ryan ᯅ

25,689 Aufrufe • vor 1 Jahr

Looking for other Vision Pro users to jump into spatial FaceTime with? Spatial Instant Messenger makes it easy! Join the directory, add friends, see who’s online, and hop into a call. Even set your status to “available” or “do not disturb.” Now on TestFlight for visionOS👇
0:32

Looking for other Vision Pro users to jump into spatial FaceTime with? Spatial Instant Messenger makes it easy! Join the directory, add friends, see who’s online, and hop into a call. Even set your status to “available” or “do not disturb.” Now on TestFlight for visionOS👇

Justin Ryan ᯅ

15,102 Aufrufe • vor 1 Jahr

Apple’s first feature-length immersive film for Vision Pro is coming. Bono: Stories of Surrender. The trailer just dropped. Launching May 30, it will put you onstage with Bono in a 180° 8K experience with Spatial Audio. Storytelling, music, and presence like never before.
2:04

Apple’s first feature-length immersive film for Vision Pro is coming. Bono: Stories of Surrender. The trailer just dropped. Launching May 30, it will put you onstage with Bono in a 180° 8K experience with Spatial Audio. Storytelling, music, and presence like never before.

Justin Ryan ᯅ

139,606 Aufrufe • vor 1 Jahr

Check out a 3D object together. Play spatial games together. Watch movies together on the same virtual screen. Here’s how to share Apple Vision Pro experiences with people nearby in #visionOS26.
2:43

Check out a 3D object together. Play spatial games together. Watch movies together on the same virtual screen. Here’s how to share Apple Vision Pro experiences with people nearby in #visionOS26.

Apple Support

36,108 Aufrufe • vor 9 Monaten

🚀 Introducing scGPT-spatial! 🧬🌍 A game-changing spatial-omic foundation model, built on the powerful scGPT framework with MoE (mixture of experts) and continually pretrained on a massive 30 million spatial single-cell profiles! 🧠 What’s the challenge? Spatial transcriptomics is next-level complex—not only must we model single-cell/spot profiles, but we also need to capture intricate spatial relationships while handling diverse sequencing protocols (imaging-based vs. sequencing-based). 🔥 Why scGPT-spatial? ✨ A Spatial-omic Foundation Model with Continual Pretraining – Built on scGPT’s robust initialization, it unlocks spatial context in tissues. ✨ SpatialHuman30M Dataset – The largest curated dataset: 30M profiles from Visium, Visium HD, Xenium, and MERFISH across 821 slides. ✨ Revolutionary MoE Decoders – A cutting-edge Mixture of Experts (MoE) architecture for protocol-aware gene expression decoding. ✨ Spatially-Aware Training Strategy – A neighborhood-based masked reconstruction approach to capture complex cell-type colocalization. ✨ Multi-Modal & Multi-Slide Integration – Seamless clustering & spatial domain identification across slides and modalities. ✨ Cell-Type Deconvolution & Gene Imputation – Unlocks cross-resolution & cross-modality harmonization with fine-tuned embeddings. 📄 Read the preprint: 💻 Explore the code/weights: #SpatialTranscriptomics #SingleCell #AIResearch #MachineLearning #SpatialData Huge shoutout to the incredible PHD students Chloe (ChloeXWang) and Haotian (Haotian Cui) for leading this groundbreaking project! 🎉 Massive thanks to our amazing co-authors Andrew, Ronald, and Hani (Hani Goodarzi) from Arc Institute—this work wouldn't have been possible without you! 👏
0:37

🚀 Introducing scGPT-spatial! 🧬🌍 A game-changing spatial-omic foundation model, built on the powerful scGPT framework with MoE (mixture of experts) and continually pretrained on a massive 30 million spatial single-cell profiles! 🧠 What’s the challenge? Spatial transcriptomics is next-level complex—not only must we model single-cell/spot profiles, but we also need to capture intricate spatial relationships while handling diverse sequencing protocols (imaging-based vs. sequencing-based). 🔥 Why scGPT-spatial? ✨ A Spatial-omic Foundation Model with Continual Pretraining – Built on scGPT’s robust initialization, it unlocks spatial context in tissues. ✨ SpatialHuman30M Dataset – The largest curated dataset: 30M profiles from Visium, Visium HD, Xenium, and MERFISH across 821 slides. ✨ Revolutionary MoE Decoders – A cutting-edge Mixture of Experts (MoE) architecture for protocol-aware gene expression decoding. ✨ Spatially-Aware Training Strategy – A neighborhood-based masked reconstruction approach to capture complex cell-type colocalization. ✨ Multi-Modal & Multi-Slide Integration – Seamless clustering & spatial domain identification across slides and modalities. ✨ Cell-Type Deconvolution & Gene Imputation – Unlocks cross-resolution & cross-modality harmonization with fine-tuned embeddings. 📄 Read the preprint: 💻 Explore the code/weights: #SpatialTranscriptomics #SingleCell #AIResearch #MachineLearning #SpatialData Huge shoutout to the incredible PHD students Chloe (ChloeXWang) and Haotian (Haotian Cui) for leading this groundbreaking project! 🎉 Massive thanks to our amazing co-authors Andrew, Ronald, and Hani (Hani Goodarzi) from Arc Institute—this work wouldn't have been possible without you! 👏

Bo Wang

59,008 Aufrufe • vor 1 Jahr

📢 OneCanvas: 3D Scene Understanding via Panoramic Reprojection We extract features from video frames and reproject them into one occlusion-free view of the whole scene that a 2D VLM reads just like a normal image. We can center this view on any viewpoint, including an agent's own pose for situated reasoning. The same projection lets us create spatial training tasks with no human annotation, solvable only by reasoning over the 3D positions of real object features placed on an otherwise empty canvas. The result is a stock 2D VLM that reasons in 3D, setting a new state of the art across spatial benchmarks at far less compute. 🌐 ▶️ Great work by Bartłomiej Baranowski & Dave Zhenyu Chen
0:44

📢 OneCanvas: 3D Scene Understanding via Panoramic Reprojection We extract features from video frames and reproject them into one occlusion-free view of the whole scene that a 2D VLM reads just like a normal image. We can center this view on any viewpoint, including an agent's own pose for situated reasoning. The same projection lets us create spatial training tasks with no human annotation, solvable only by reasoning over the 3D positions of real object features placed on an otherwise empty canvas. The result is a stock 2D VLM that reasons in 3D, setting a new state of the art across spatial benchmarks at far less compute. 🌐 ▶️ Great work by Bartłomiej Baranowski & Dave Zhenyu Chen

Matthias Niessner

25,093 Aufrufe • vor 1 Monat

Alibaba presents MIMO Controllable Character Video Synthesis with Spatial Decomposed Modeling Character video synthesis aims to produce realistic videos of animatable characters within lifelike scenes. As a fundamental problem in the computer vision and graphics community, 3D works typically require multi-view captures for per-case training, which severely limits their applicability of modeling arbitrary characters in a short time. Recent 2D methods break this limitation via pre-trained diffusion models, but they struggle for pose generality and scene interaction. To this end, we propose MIMO, a novel framework which can not only synthesize character videos with controllable attributes (i.e., character, motion and scene) provided by simple user inputs, but also simultaneously achieve advanced scalability to arbitrary characters, generality to novel 3D motions, and applicability to interactive real-world scenes in a unified framework. The core idea is to encode the 2D video to compact spatial codes, considering the inherent 3D nature of video occurrence. Concretely, we lift the 2D frame pixels into 3D using monocular depth estimators, and decompose the video clip to three spatial components (i.e., main human, underlying scene, and floating occlusion) in hierarchical layers based on the 3D depth. These components are further encoded to canonical identity code, structured motion code and full scene code, which are utilized as control signals of synthesis process. The design of spatial decomposed modeling enables flexible user control, complex motion expression, as well as 3D-aware synthesis for scene interactions. Experimental results demonstrate effectiveness and robustness of the proposed method.
1:29

Alibaba presents MIMO Controllable Character Video Synthesis with Spatial Decomposed Modeling Character video synthesis aims to produce realistic videos of animatable characters within lifelike scenes. As a fundamental problem in the computer vision and graphics community, 3D works typically require multi-view captures for per-case training, which severely limits their applicability of modeling arbitrary characters in a short time. Recent 2D methods break this limitation via pre-trained diffusion models, but they struggle for pose generality and scene interaction. To this end, we propose MIMO, a novel framework which can not only synthesize character videos with controllable attributes (i.e., character, motion and scene) provided by simple user inputs, but also simultaneously achieve advanced scalability to arbitrary characters, generality to novel 3D motions, and applicability to interactive real-world scenes in a unified framework. The core idea is to encode the 2D video to compact spatial codes, considering the inherent 3D nature of video occurrence. Concretely, we lift the 2D frame pixels into 3D using monocular depth estimators, and decompose the video clip to three spatial components (i.e., main human, underlying scene, and floating occlusion) in hierarchical layers based on the 3D depth. These components are further encoded to canonical identity code, structured motion code and full scene code, which are utilized as control signals of synthesis process. The design of spatial decomposed modeling enables flexible user control, complex motion expression, as well as 3D-aware synthesis for scene interactions. Experimental results demonstrate effectiveness and robustness of the proposed method.

AK

148,998 Aufrufe • vor 1 Jahr

Introducing WorldView 3D, a first-of-its-kind satellite tasking product that delivers up-to-date 3D ground truth anywhere on Earth. From GPS-denied autonomy and intelligence analysis to consumer-grade mapping and disaster response, the world's most important missions increasingly depend on accurate, up-to-date 3D terrain. But for years, keeping 3D maps current at global scale hasn't been possible. WorldView 3D changes that. Built on Vantor’s trusted spatial foundation, our new tasking capability empowers customers to task and receive updated 3D data within 24 hours of image collection. For missions that require greater fidelity, they can also produce high-definition 3D maps anywhere in the world. 3D is the future of spatial intelligence, and Vantor is leading the change. Our trusted spatial foundation already includes 100 million sq km of the world mapped inhighly accurate 3D. Now customers can update the locations that matter most with the speed, scale, and fidelity required for critical missions. Read the full announcement:
0:35

Introducing WorldView 3D, a first-of-its-kind satellite tasking product that delivers up-to-date 3D ground truth anywhere on Earth. From GPS-denied autonomy and intelligence analysis to consumer-grade mapping and disaster response, the world's most important missions increasingly depend on accurate, up-to-date 3D terrain. But for years, keeping 3D maps current at global scale hasn't been possible. WorldView 3D changes that. Built on Vantor’s trusted spatial foundation, our new tasking capability empowers customers to task and receive updated 3D data within 24 hours of image collection. For missions that require greater fidelity, they can also produce high-definition 3D maps anywhere in the world. 3D is the future of spatial intelligence, and Vantor is leading the change. Our trusted spatial foundation already includes 100 million sq km of the world mapped inhighly accurate 3D. Now customers can update the locations that matter most with the speed, scale, and fidelity required for critical missions. Read the full announcement:

Vantor

16,030 Aufrufe • vor 23 Tagen

AI 3D workflows for web are getting scary good. Here is a demo with a large splat background (+LoD), mesh character, spatial audio, VR support, and lighting. I was able to create it in a few hours (repo in reply). built with Three.js spark World Labs Audio on :)
1:03

AI 3D workflows for web are getting scary good. Here is a demo with a large splat background (+LoD), mesh character, spatial audio, VR support, and lighting. I was able to create it in a few hours (repo in reply). built with Three.js spark World Labs Audio on :)

martin_casado

82,439 Aufrufe • vor 7 Monaten

Designed in collaboration with our pro teams, designed for you 💫 We've been cooking with Sony Electronics, and it's finally time to show you what we've been working on. Get ready for spatial audio, crystal clear comms, and all-day comfort with INZONE Buds:
0:44

Designed in collaboration with our pro teams, designed for you 💫 We've been cooking with Sony Electronics, and it's finally time to show you what we've been working on. Get ready for spatial audio, crystal clear comms, and all-day comfort with INZONE Buds:

FNATIC

93,634 Aufrufe • vor 2 Jahren

WE DID IT! +100,000 OVRMAPS 🚀 A major milestone in decentralized spatial computing. A huge thank you to our incredible community of mappers and our technical team! ↳ 30M sqm of 3D-mapped terrain ↳ 55TB of image data processed with cutting-edge AI models ↳ Powered by DePIN and a global network of mappers This is the future of Spatial Computing. Let’s break it down: 🧵👇
0:28

WE DID IT! +100,000 OVRMAPS 🚀 A major milestone in decentralized spatial computing. A huge thank you to our incredible community of mappers and our technical team! ↳ 30M sqm of 3D-mapped terrain ↳ 55TB of image data processed with cutting-edge AI models ↳ Powered by DePIN and a global network of mappers This is the future of Spatial Computing. Let’s break it down: 🧵👇

Over the Reality 🌐

493,928 Aufrufe • vor 1 Jahr