Edgar Sucar @SucarEdgar
Postdoc @Oxford_VGG PhD Dyson Robotics Lab at Imperial College edgarsucar.github.io Oxford, UK Joined April 2017-
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Delighted to share the first project of my PhD, "Transient Neural Radiance Fields for Lidar View Synthesis and 3D Reconstruction". We show unprecedented capabilities of synthesizing novel lidar scans from as few as 2 input views! 🖥️anaghmalik.com/TransientNeRF
Congratulations to Edgar who passed his PhD viva today, and thanks to examiners @tolga_birdal and José María Montiel! A reminder of Edgar's iMAP, a landmark as the first real-time neural field SLAM system from #ICCV2021.
Congratulations to Edgar who passed his PhD viva today, and thanks to examiners @tolga_birdal and José María Montiel! A reminder of Edgar's iMAP, a landmark as the first real-time neural field SLAM system from #ICCV2021.
vMAP: Vectorised Object Mapping for Neural Field SLAM, new at #CVPR2023! Each object is represented by a separate MLP, optimised in parallel via vectorised training. Full info: kxhit.github.io/vMAP Dyson Robotics Lab, Imperial College, @liu_shikun, Marwan Taher, @AjdDavison.
Excited to announce "Learning a Depth Covariance Function" with @AjdDavison. A flexible framework for a variety of geometric vision tasks, such as dense monocular visual odometry shown below. Dyson Robotics Lab, Imperial College Project page: edexheim.github.io/depth_cov/ #CVPR2023
What is ChatGPT doing ... and why does it work? From the lore of neural nets to what Aristotle didn't get to ... here's my version of the story: writings.stephenwolfram.com/2023/02/what-i…
Our work on leveraging general pre-trained feature extractors for open-set real-time scene understanding has been accepted for #ICRA2023! Joint work with @SucarEdgar @AjdDavison Check out project page: makezur.github.io/FeatureRealist…
Our work on leveraging general pre-trained feature extractors for open-set real-time scene understanding has been accepted for #ICRA2023! Joint work with @SucarEdgar @AjdDavison Check out project page: makezur.github.io/FeatureRealist…
If you're at CORL this week in NZ come and meet @iainhaughton and @Ed__Johns and see Iain's presentation in the oral session on Saturday. Dense, fully automatic segmentation of scene properties like softness via real-time neural field training; no priors! It's iLabel for robots.
If you're at CORL this week in NZ come and meet @iainhaughton and @Ed__Johns and see Iain's presentation in the oral session on Saturday. Dense, fully automatic segmentation of scene properties like softness via real-time neural field training; no priors! It's iLabel for robots. https://t.co/aJ7EzqyZ0b
#CORL2022 oral: mapping non-visual properties (material, softness, force) from very few point sensor tests. iLabel-like neural field produces dense maps + guides actions. Live, autonomous, no priors! @iainhaughton et al, @Dyson @ICComputing. Paper/video: ihaughton.github.io/RobE/
New: Feature-realistic neural fusion for real-time, open set scene understanding. Our neural field renders to feature space, enabling real-time grouping and segmentation of similar objects or parts from ultra-sparse, online interaction. Dyson Robotics Lab. makezur.github.io/FeatureRealist…
"A Year" AI animation artwork made in colab using my custom stable 3D animation algorithm on top of #stablediffusion model. In the thread I share some details about the algo and when i plan to release it, and talk about the joy and future of AI filmmaking 🎶 DakhaBrakha - Vesna
cool work by Dominic Maggio and collaborators on real-time robot localization using Neural Radiance Fields (NeRF) with Monte Carlo Localization: youtu.be/yIgl3kbpbXY (link to full paper in the video description) #mitSparkLab #NeRF #neuralFields #robotics #localization
Glad to see @SucarEdgar, @AjdDavison "Implicit Mapping and Positioning in Real-time" highlighted in the Neural Fields in Robotics tutorial at #cvpr2022 Take a look at the project here edgarsucar.github.io/iMAP/
NICE-SLAM: a hybrid representation of feature voxels plus MLP allows neural mapping to scale to larger scenes. Similar representation to Instant-NGP, minus hashing and with a pretrained decoder. Wondering what is the advantage of pretraining the MLP decoder?
NICE-SLAM: a hybrid representation of feature voxels plus MLP allows neural mapping to scale to larger scenes. Similar representation to Instant-NGP, minus hashing and with a pretrained decoder. Wondering what is the advantage of pretraining the MLP decoder?
iSDF shows how to reconstruct a full signed distance function through optimisation of a Neural Field, by bounding SDF predictions with depth surface measurements. This representation is particularly exciting for applications in robot planning.
iSDF shows how to reconstruct a full signed distance function through optimisation of a Neural Field, by bounding SDF predictions with depth surface measurements. This representation is particularly exciting for applications in robot planning.
Andrew Davison @AjdDavison
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Dmytro Mishkin 🇺�.. @ducha_aiki
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Andrew Davison @AjdDavison
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Muchas felicidades a mi hijo Rafael por su premio a la excelencia académica en la facultad de derecho de la Universidad de Guanajuato!
Reconstructing Ignatius (Tanks&Temples) from 7,843 images, starting from raw images without intrinsics, in one hour on a V100. #ACEZero
Faster colmap MVS available from docker pull parskatt/colmap:12.2.2-sm_80
This is their “test prototype” they are showing off. It seems like they ripped my design files directly from here: hackaday.io/project/186410… And I’m 90% sure they’re using my software to fly this thing too. It flies with all the same little quirks I’d expect from my code.
Alright Twitter, how petty should I get over on LinkedIn, on a scale of 1-10? Newly unveiled revolutionary, groundbreaking, and 100% original drone design announced today!
While waiting for the open source approval, we have upgraded VGGSfM from v1 to v1.1. The new one is much more accurate, particularly with strict thresholds such as AUC@3. Additionally, it's twice faster during inference. @davnov134 @chrirupp @n_karaev
@WayneINR @AjdDavison @LourdesAgapito Here are the slides of my recent invited talk about CroCo + DUSt3R + MASt3R files.europe.naverlabs.com/index.php/file… Note: It's a pdf, i know the videos won't work but there's really nothing hitherto unseen. I can point to where to find each individual video upon request.
@AjdDavison Same goes in the other direction. I wasn’t expecting that many excellent, really top-notch papers and demos. Super interesting research overall! Also really liked the atmosphere in your lab, for sure one of the best lab i visited
I just updated my Meta glasses and it does everything I see Humane users wanting the Ai Pin to do. Low latency Multimodal works flawlessly Everything **just works** on my $299 glasses with no subscription @MKBHD didn’t kill Humane, Zuck did 😂
Meta's Ray-Ban glasses now have multimodal AI
📢 Code release for 𝗗𝗦𝗜𝗡𝗘 (#CVPR2024 - Oral) DSINE gives you surface normal prediction (+ uncertainty) in real-time. We have released the code for training, testing, and running real-time demos. Try it yourself! github.com/baegwangbin/DS…
A lens that brings objects back to an 8-bit status [🔍 Hakusi_Katei]
Who else learned more from this than ~2/3rds of undergrad?👀
Working moderately hard over long periods of time will take you much further than getting overexcited, trading your long-term health against short-term results, and burning out. Play the long-term game, that’s the only game that matters.
With satellite imagery, it’s hard to get labels. Solution? DINOv2! WRI+Meta trained a satellite DINOv2 for tree height estimation. They created an interactive map of tree height of the whole globe (!) at 1-meter res (!): …toring-okw37.projects.earthengine.app/view/canopyhei… Quizz: Can you recognize this city?
his Coca-Cola can appears reddish, though it consists of black and white random dots.
Ray-Ban Meta smart glasses just got a massive Multimodal upgrade - Meta AI with Vision It doesn't just take speech input, it can now answer questions about what you are seeing. Here are 8 features that is now possible 1. Ask about what you are seeing
Thanks for sharing :) TLDR: Introducing an image evaluation method that assesses rendered images via images from other viewpoints, eliminating the need for ground truth. Primary use: assessing novel views in NVS tasks. ⛳️ crossscore.active.vision 📄 arxiv.org/abs/2404.14409
CrossScore: Towards Multi-View Image Evaluation and Scoring @ziruiwang_, @wenjing_bian, @omkarparkhi, @CarlYuhengRen, @viprad tl;dr: cross-attention+data from NVS optimisation->compare query image and multiple views of the same scene->IQA without GT arxiv.org/pdf/2404.14409…
FlowMap: High-Quality Camera Poses, Intrinsics, and Depth via Gradient Descent arxiv.org/abs/2404.15259 Project: cameronosmith.github.io/flowmap/
Coming back from London, after being kindly invited for a talk about DUSt3R + MASt3R in the Dyson lab of @AjdDavison at Imperial college and in the 3DV team of @LourdesAgapito at UCL. Had insightful discussions with all lab’s members, this was truly a great time spent there ❤️
📢📢📢 𝐁𝐀𝐍𝐅: 𝐁𝐚𝐧𝐝-𝐥𝐢𝐦𝐢𝐭𝐞𝐝 𝐍𝐞𝐮𝐫𝐚𝐥 𝐅𝐢𝐞𝐥𝐝𝐬 𝐟𝐨𝐫 𝐋𝐞𝐯𝐞𝐥𝐬 𝐨𝐟 𝐃𝐞𝐭𝐚𝐢𝐥 𝐑𝐞𝐜𝐨𝐧𝐬𝐭𝐫𝐮𝐜𝐭𝐢𝐨𝐧 lead by Ahan Shabanov (@ahan_sh) at #CVPR2024 Wonder how to get frequency control in neural fields? This is for you: theialab.github.io/banf
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