#cvpr2023 — Public Fediverse posts
Live and recent posts from across the Fediverse tagged #cvpr2023, aggregated by home.social.
-
During #CVPR2023 @MetaAI
presented Project Aria, a project that utilizes a sensor packed headset to help researchers gather data from the user’s perspective. As a part of their tutorials they included a presentation on how to use Rerun for visualizing multi-modal data! 🤯 -
What is the latest research in quantifying animal movement and behavior?
I wrote down a detailed overview here, based on what I saw at CVPR this year:
https://writings.lambdaloop.com/posts/cv4animals-2023/#PoseEstimation #animals #computervision #cvpr #cvpr2023 #neuroscience
-
Enjoy Image Matching Challenge 2023 recap:
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2023/07/05/IMC2023-Recap.html
tl;dr:
- SfM is not solved
- global desc similarity is hard
- orientation invariance for SuperGlue is easy
- PixSfM is good idea, but need follow-ups
- KeyNetAffNet
@kornia_foss rocks -
Enjoy Image Matching Challenge 2023 recap:
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2023/07/05/IMC2023-Recap.html
tl;dr:
- SfM is not solved
- global desc similarity is hard
- orientation invariance for SuperGlue is easy
- PixSfM is good idea, but need follow-ups
- KeyNetAffNet
@kornia_foss rocks -
Enjoy Image Matching Challenge 2023 recap:
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2023/07/05/IMC2023-Recap.html
tl;dr:
- SfM is not solved
- global desc similarity is hard
- orientation invariance for SuperGlue is easy
- PixSfM is good idea, but need follow-ups
- KeyNetAffNet
@kornia_foss rocks -
Enjoy Image Matching Challenge 2023 recap:
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2023/07/05/IMC2023-Recap.html
tl;dr:
- SfM is not solved
- global desc similarity is hard
- orientation invariance for SuperGlue is easy
- PixSfM is good idea, but need follow-ups
- KeyNetAffNet
@kornia_foss rocks -
Enjoy Image Matching Challenge 2023 recap:
https://ducha-aiki.github.io/wide-baseline-stereo-blog/2023/07/05/IMC2023-Recap.html
tl;dr:
- SfM is not solved
- global desc similarity is hard
- orientation invariance for SuperGlue is easy
- PixSfM is good idea, but need follow-ups
- KeyNetAffNet
@kornia_foss rocks -
HierVL is a new #AI approach injecting semantics into visual representations by capturing long-term and short-term associations in video-language embeddings capturing both 'what' and 'why' of human actions. 🤯
-
PanoHead: a breakthrough in 3D human head synthesis
This novel generative #AI model produces 360° view-consistent images of full heads and overcomes limitations in existing methods by leveraging 3D GANs and innovative image alignment techniques. 🤩
-
Rodney Brooks #CVPR2023 keynote about his PhD in the 70s: “In four years I processed three images.”
-
made it to vancouver for #cvpr2023, really excited to host our 5th annual VizWiz Workshop, with three outstanding keynote speakers -- representing users, researchers, and industry --
-
Happy to announce that our paper "Inferring the Past: A Combined CNN-LSTM Deep Learning Framework To Fuse Satellites for Historical Inundation Mapping" was accepted at CVPR workshop Earthvision!
-
will be at #cvpr2023 mostly hanging out at the #cv4animals workshop. if anyone wants to meet up to talk about the intersection of #machinelearning and #conservation let me know.
-
We released our Neural Parametric Head Models (NPHM) dataset from our #CVPR2023 paper!
It includes over 5600 high-fidelity 3D scans of human heads from 272 subjects - all publicly available!
Check it out!
https://simongiebenhain.github.io/NPHM/We've also released the NPHM code: https://github.com/SimonGiebenhain/NPHM
We provide several examples and a small demo how to use our dataset. It's now super easy to build your own parametric face/head model!
Great work by Simon, Tobias, Markos Martin Lourdes!
-
D2Former: Jointly Learning Hierarchical Detectors and Contextual Descriptors via Agent-Based Transformers
Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu
tl;dr: no idea how that works, hierarchical attention something. No eval on #IMC
https://openaccess.thecvf.com/content/CVPR2023/papers/He_D2Former_Jointly_Learning_Hierarchical_Detectors_and_Contextual_Descriptors_via_Agent-Based_CVPR_2023_paper.pdf
#CVPR2023
#computervision #deeplearning
#dmytrotweetsaboutDL -
D2Former: Jointly Learning Hierarchical Detectors and Contextual Descriptors via Agent-Based Transformers
Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu
tl;dr: no idea how that works, hierarchical attention something. No eval on #IMC
https://openaccess.thecvf.com/content/CVPR2023/papers/He_D2Former_Jointly_Learning_Hierarchical_Detectors_and_Contextual_Descriptors_via_Agent-Based_CVPR_2023_paper.pdf
#CVPR2023
#computervision #deeplearning
#dmytrotweetsaboutDL -
D2Former: Jointly Learning Hierarchical Detectors and Contextual Descriptors via Agent-Based Transformers
Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu
tl;dr: no idea how that works, hierarchical attention something. No eval on #IMC
https://openaccess.thecvf.com/content/CVPR2023/papers/He_D2Former_Jointly_Learning_Hierarchical_Detectors_and_Contextual_Descriptors_via_Agent-Based_CVPR_2023_paper.pdf
#CVPR2023
#computervision #deeplearning
#dmytrotweetsaboutDL -
D2Former: Jointly Learning Hierarchical Detectors and Contextual Descriptors via Agent-Based Transformers
Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu
tl;dr: no idea how that works, hierarchical attention something. No eval on #IMC
https://openaccess.thecvf.com/content/CVPR2023/papers/He_D2Former_Jointly_Learning_Hierarchical_Detectors_and_Contextual_Descriptors_via_Agent-Based_CVPR_2023_paper.pdf
#CVPR2023
#computervision #deeplearning
#dmytrotweetsaboutDL -
D2Former: Jointly Learning Hierarchical Detectors and Contextual Descriptors via Agent-Based Transformers
Jianfeng He, Yuan Gao, Tianzhu Zhang, Zhe Zhang, Feng Wu
tl;dr: no idea how that works, hierarchical attention something. No eval on #IMC
https://openaccess.thecvf.com/content/CVPR2023/papers/He_D2Former_Jointly_Learning_Hierarchical_Detectors_and_Contextual_Descriptors_via_Agent-Based_CVPR_2023_paper.pdf
#CVPR2023
#computervision #deeplearning
#dmytrotweetsaboutDL -
SFD2: Semantic-guided Feature Detection and Description
Fei Xue, Ignas Budvytis, Roberto Cipolla
tl;dr: more principled approach to use segmentation for image matching, than class-name filtering.
-
Check out "Learning Neural Parametric Head Models"!
One of the best parts of writing a paper is the collaboration with great talents. At Synthesia we are working with TUM+UCL and our first publication will be presented at #CVPR2023 🎉 Special thanks to the first author Simon (https://simongiebenhain.github.io) for the fantastic execution.
Project page: https://simongiebenhain.github.io/NPHM/
-
Excited to share "Learning Neural Parametric Head Models" #CVPR2023!
We capture over 5200 high-quality 3D human head scans from which we build a neural parametric head model that disentangles & expressions and deformations.
Core of our representation is an ensemble of local MLPs to facilitate high geometric detail. We will release the entire data asap!
https://simongiebenhain.github.io/NPHM/
https://youtu.be/0mDk2tFOJCg -
Camera frame registration with little or no overlap?
Check out Can's ObjectMatch: We leverage object semantics to find indirect correspondences between frames. Great for any SLAM and SfM pose optimization!
Video: https://youtu.be/kuXoKVrzURk
Project: https://cangumeli.github.io/ObjectMatch/ -
Image Matching Challenge 2023 starts NOW!
Task: 3D reconstructions from 10-100 images
Entry Deadline: June 6, 2023.
Prize Money: $50,000#IMC2023 #CVPR2023
#deeplearning #computervisionhttps://kaggle.com/competitions/image-matching-challenge-2023/overview
-
Excited to share Norman's DiffRF: Rendering-guided 3D Radiance Field Diffusion #CVPR2023 highlight!
2D diffusion is great, but what about 3D? We show radiance field diffusion with rendering guidance for consistent and editable 3D synthesis.
Video: http://youtu.be/qETBcLu8SUk
Project: sirwyver.github.io/DiffRFGreat collaboration with Peter's group at Meta!
-
PMatch: Paired Masked Image Modeling for Dense Geometric Matching
Shengjie Zhu, Xiaoming Liu
tl;dr: cross-view patch reconstruction pre training, then use (modified) LoFTR for two view matching.
Code repo is not yet created.
https://arxiv.org/abs/2303.17342.pdf
#computervision #deeplearning
#dmytrotweetsaboutDL #CVPR2023 -
3D Line Mapping Revisited
Shaohui Liu, Yifan Yu, Rémi Pautrat, Marc Pollefeys, Viktor Larsson
tl;dr: Point-guided line SfM with scale-invariant scoring -> profit. Even improves SuperPoint + Colmap bundle adjustment
https://arxiv.org/abs/2303.17504.pdf
#computervision #deeplearning
#dmytrotweetsaboutDL #CVPR2023 -
Working on an interesting fine-grained problem, but the #ICCV2023 deadline is approaching too quickly?
The FGVC10 paper submission website is now open!https://sites.google.com/view/fgvc10/submission
Deadline: March 20
-
Working on an interesting fine-grained problem, but the #ICCV2023 deadline is approaching too quickly?
The FGVC10 paper submission website is now open!https://sites.google.com/view/fgvc10/submission
Deadline: March 20
-
Working on an interesting fine-grained problem, but the #ICCV2023 deadline is approaching too quickly?
The FGVC10 paper submission website is now open!https://sites.google.com/view/fgvc10/submission
Deadline: March 20
-
Working on an interesting fine-grained problem, but the #ICCV2023 deadline is approaching too quickly?
The FGVC10 paper submission website is now open!https://sites.google.com/view/fgvc10/submission
Deadline: March 20
-
Working on an interesting fine-grained problem, but the #ICCV2023 deadline is approaching too quickly?
The FGVC10 paper submission website is now open!https://sites.google.com/view/fgvc10/submission
Deadline: March 20
-
NICE! High-Res Facial Appearance Capture from Polarized Smartphone Images 🤳
This approach uses a smartphone with a cheap polarization foil to capture facial textures in dark settings to then create photo-realistic 3D #DigitalHumans 👉https://dazinovic.github.io/polface/
-
Great News! FGVC10 (10th Workshop on Fine-Grained Visual Categorization) was accepted to CVPR 2023 and will take place in Vancouver. Interested in fine-grained learning and its applications? Consider submitting your paper to FGVC10.
Deadline: March 20.
More information on the website: https://sites.google.com/view/fgvc10