Throws machine learning at traditional computer vision pipelines to see what sticks. Differentiates the non-differentiable.
📍Europe 🔗 http://ebrach.github.io
Gives you, e.g., a RGB-D version of ACE0. In the snipped below, I jointly reconstruct multiple RGB-D scans of ScanNet.
github.com/nianticlabs/...
Gives you, e.g., a RGB-D version of ACE0. In the snipped below, I jointly reconstruct multiple RGB-D scans of ScanNet.
github.com/nianticlabs/...
I will give three (very different) talks at workshops and tutorials, see info below.
We also present two papers, ACE-G and SCR Priors.
And it's the 10th (!) anniversary of the R6D workshop, which we co-organize.
I will give three (very different) talks at workshops and tutorials, see info below.
We also present two papers, ACE-G and SCR Priors.
And it's the 10th (!) anniversary of the R6D workshop, which we co-organize.
Can we learn what a successful reconstruction looks like, and use this knowledge when reconstructing new scenes?
Explainer: youtu.be/RkV6U5xYc20
Project Page: nianticspatial.github.io/scr-priors
Inspiring work by Wenjing Bian et al.!
Can we learn what a successful reconstruction looks like, and use this knowledge when reconstructing new scenes?
Explainer: youtu.be/RkV6U5xYc20
Project Page: nianticspatial.github.io/scr-priors
Inspiring work by Wenjing Bian et al.!
We disentangle coordinate regression and latent map representation which lets us pre-train the regressor to generalize from mapping data to difficult query images.
Page: nianticspatial.github.io/ace-g/
Stellar work by Leonard Bruns et al.!
We disentangle coordinate regression and latent map representation which lets us pre-train the regressor to generalize from mapping data to difficult query images.
Page: nianticspatial.github.io/ace-g/
Stellar work by Leonard Bruns et al.!
Each token is combined with its ray embedding. Hence, FastForward operates on samples of visual tokens in scene space.
Each token is combined with its ray embedding. Hence, FastForward operates on samples of visual tokens in scene space.
⏩ Get poses for your mapping images, e.g. via SLAM in real time.
⏩ Build a retrieval index in seconds.
⏩ FastForward predicts the relative pose between a query image and all retrieved images in one forward pass.
⏩ Get poses for your mapping images, e.g. via SLAM in real time.
⏩ Build a retrieval index in seconds.
⏩ FastForward predicts the relative pose between a query image and all retrieved images in one forward pass.
nianticspatial.github.io/fastforward/
Work by @axelbarroso.bsky.social, Tommaso Cavallari and Victor Adrian Prisacariu.
nianticspatial.github.io/fastforward/
Work by @axelbarroso.bsky.social, Tommaso Cavallari and Victor Adrian Prisacariu.
cmp.felk.cvut.cz/sixd/worksho...
The accompanying challenge is still open for submissions until Oct 1st. And the workshop also still accepts non-proceeding paper submission!
cmp.felk.cvut.cz/sixd/worksho...
The accompanying challenge is still open for submissions until Oct 1st. And the workshop also still accepts non-proceeding paper submission!
@sattlertorsten.bsky.social et al.
Now I have 5 months to get used to the fact of giving a talk after Richard Hartley 🙈
@sattlertorsten.bsky.social et al.
Now I have 5 months to get used to the fact of giving a talk after Richard Hartley 🙈
Your chance to shine on the task mentioned above. But beware that BOP is one step ahead already, by adding another set of nightmarish datasets. 👻
Your chance to shine on the task mentioned above. But beware that BOP is one step ahead already, by adding another set of nightmarish datasets. 👻
BOP is a benchmark for 6D object pose estimation, with a new challenge organised yearly.
Community: Model-based 6D localisation? Pff, easy-peasy. 💪
BOP: Ok. Model-free 6D detection on the datasets below 👇
Community: 🙈 (0 entries submitted)
BOP is a benchmark for 6D object pose estimation, with a new challenge organised yearly.
Community: Model-based 6D localisation? Pff, easy-peasy. 💪
BOP: Ok. Model-free 6D detection on the datasets below 👇
Community: 🙈 (0 entries submitted)
See e.g. faculty.sites.iastate.edu/jia/files/in...
See e.g. faculty.sites.iastate.edu/jia/files/in...