Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: T6D-Direct: Transformers for Multi-Object 6D Pose Direct Regression   6D pose estimation is the task of predicting the translation and orientation
of objects in a given input image, which is a crucial prerequisite for many
robotics and augmented reality applications. Lately, the Transformer Network
architecture, equipped with a multi-head self-attention mechanism, is emerging
to achieve state-of-the-art results in many computer vision tasks. DETR, a
Transformer-based model, formulated object detection as a set prediction
problem and achieved impressive results without standard components like region
of interest pooling, non-maximal suppression, and bounding box proposals. In
this work, we propose T6D-Direct, a real-time single-stage direct method with a
transformer-based architecture built on DETR to perform 6D multi-object pose
direct estimation. We evaluate the performance of our method on the YCB-Video
dataset. Our method achieves the fastest inference time, and the pose
estimation accuracy is comparable to state-of-the-art methods.

20
The categories of this paper are: acc-phys
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
24
The categories of this paper are: dg-ga
28
The categories of this paper are: alg-geom
35
The categories of this paper are: mtrl-th
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
15
The categories of this paper are: nucl-ex
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The categories of this paper are: patt-sol
17
The categories of this paper are: q-fin
18
The categories of this paper are: econ
9
The categories of this paper are: nlin
0
The categories of this paper are: hep-ph
34
The categories of this paper are: chem-ph
6
The categories of this paper are: astro-ph