Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sim2Real Object-Centric Keypoint Detection and Description   Keypoint detection and description play a central role in computer vision.
Most existing methods are in the form of scene-level prediction, without
returning the object classes of different keypoints. In this paper, we propose
the object-centric formulation, which, beyond the conventional setting,
requires further identifying which object each interest point belongs to. With
such fine-grained information, our framework enables more downstream
potentials, such as object-level matching and pose estimation in a clustered
environment. To get around the difficulty of label collection in the real
world, we develop a sim2real contrastive learning mechanism that can generalize
the model trained in simulation to real-world applications. The novelties of
our training method are three-fold: (i) we integrate the uncertainty into the
learning framework to improve feature description of hard cases, e.g.,
less-textured or symmetric patches; (ii) we decouple the object descriptor into
two output branches -- intra-object salience and inter-object distinctness,
resulting in a better pixel-wise description; (iii) we enforce cross-view
semantic consistency for enhanced robustness in representation learning.
Comprehensive experiments on image matching and 6D pose estimation verify the
encouraging generalization ability of our method from simulation to reality.
Particularly for 6D pose estimation, our method significantly outperforms
typical unsupervised/sim2real methods, achieving a closer gap with the fully
supervised counterpart. Additional results and videos can be found at
https://zhongcl-thu.github.io/rock/

29
The categories of this paper are: funct-an
7
The categories of this paper are: hep-th
26
The categories of this paper are: bayes-an
12
The categories of this paper are: nucl-th
23
The categories of this paper are: solv-int
10
The categories of this paper are: q-bio
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
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The categories of this paper are: dg-ga
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The categories of this paper are: comp-gas
14
The categories of this paper are: math-ph
21
The categories of this paper are: adap-org
11
The categories of this paper are: hep-lat
6
The categories of this paper are: astro-ph
16
The categories of this paper are: stat
25
The categories of this paper are: patt-sol