Erroll Wood @errollw
Staff SWE at Google, working on Digital Humans for AR & VR errollw.com Cambridge, UK Joined January 2011-
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Intelligent eyewear is coming this fall! ✨ It was a privilege to be onstage at #GoogleIO to show our new audio glasses with #Gemini and share a first look at two designs from the upcoming collections. I’m incredibly proud of our team and the partnership with @SamsungMobile and iconic eyewear brands @WarbyParker and @_GentleMonster_ to bring hands-free help to your everyday life. Read more: goo.gle/intelligenteye… Watch I/O Keynote: youtube.com/live/wYSncx9zL…
Meet D4RT 🎯 A unified model for next-gen scene reconstruction and tracking. 🧠 The Secret Sauce: Incredible results thanks in part to diverse, realistic synthetic data from our team. The results are wild. 🤯
We're helping AI to see the 3D world in motion as humans do. 🌐 Enter D4RT: a unified model that turns video into 4D representations faster than previous methods - enabling it to understand space and time. This is how it works 🧵
#SyntheticData powers cutting-edge algorithms on #AndroidXR like Hand Tracking, Face Tracking, and more. 🦾 At #CVPR2025 ? Attend our tutorial (June 12th) to dive deep into Android XR's Perception stack. Full schedule here: augmentedperception.github.io/cvpr2025/
Excited to finally share #AndroidXR #Moohan with the world. We're just getting started 💪😎
#AndroidXR is officially here! 🎉 Thrilled to see the developer excitement and passion to build immersive experiences. Huge thanks to the @GoogleARVR team and our incredible partners @SamsungMobile and @Qualcomm and more. ➡️ blog.google/products/andro…
It turns out that a synthetic-only face prior is great for novel view synthesis 🦾. If you're heading to SIGGRAPH Asia 🇯🇵, don't miss Cᴀꜰᴄᴀ. Great work, @mc_buehler!
A purely synthetic face prior can generalize to casual in-the-wild captures and stylized faces 🤯 I'm happy to share our @SIGGRAPHAsia paper “Cafca: High-quality Novel View Synthesis of Expressive Faces from Casual Few-shot Captures.” syntec-research.github.io/Cafca/
Coming to #CVPR23? Come to my talk on Sunday morning at the GAZE workshop gazeworkshop.github.io/2023/ to hear about Synthetic Data for Gaze Estimation & More. Find out what worked 🙌🏻, what didn't 🤔, and what's next 🚀.
At #ECCV2022? Come try our our face tracker, powered by #syntheticdata and some real-time model-fitting magic 🪄. 🖼️ Poster 59 in Thursday's morning session. 🔗 microsoft.github.io/DenseLandmarks/
Excited to share our work on #syntheticdata, generating dynamic expression-based wrinkles for digital faces, to appear at #WACV2023! With @Friggog, @errollw, and Tadas Baltrušaitis @Microsoft Mixed Reality & AI Cambridge 📝arxiv.org/abs/2210.03529 🧵1/8
New Video - Microsoft's New AI: Virtual Humans Became Real! 🤯 youtu.be/6-FESfXHF5s #ai
@skynetislov3 We hear you, and understand! We have nothing more to share at this point in time, but keep watching this space 🙂
Very proud to share more about our work on 𝗗𝗲𝗻𝘀𝗲 𝗙𝗮𝗰𝗲 𝗟𝗮𝗻𝗱𝗺𝗮𝗿𝗸𝘀, which will appear at #ECCV2022. Check it out! 👇 🔗 microsoft.github.io/DenseLandmarks/ 🎥 youtube.com/watch?v=M8NNyt… 📝 arxiv.org/abs/2204.02776
@designerzen We have nothing more to share at this time, but keep watching this space 🙂
@cvtalks That's a really cool dataset! The community will love it! However, I'd argue that #syntheticdata can give you more consistent labels, and greater training data diversity.
@afromero I'm not sure, but please do reach out to the organizers of the workshop to find out :)
Join me tomorrow at the SyntML workshop at #CVPR2022 to hear about how #syntheticdata helps us solve all sorts of face-related computer vision problems. These aren't toy problems, they are the real deal! syntml-cvpr2022-workshop.github.io
@Babak_Taati @KITE_UHN @KITETrainees @AGEWELL_NCE Do ping me with any questions and I will do my best to answer :)
@91amin91 Mediapipe is awesome, and I love their Attention Mesh design. But I think our synthetic training data is just better than their real data😉 We have nothing to share at this time unfortunately, but please stay tuned for further announcements🙂
I'm delighted to share our work on dense landmarks! arxiv.org/abs/2204.02776 🌟 Dense landmarks are all you need for accurate 3D face reconstruction and performance capture 💪 No surprise: the secret sauce is synthetic data 🏃 It's fast, running at 150FPS on a single CPU thread
@MrCatid We have nothing to share at this time unfortunately, but please stay tuned for further announcements🙂
@cubaneth We have nothing to share at this time unfortunately, but please stay tuned for further announcements🙂
@Wiz64268099 We have nothing to share at this time unfortunately, but please stay tuned for further announcements🙂
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