14 research outputs found
SPNet: Deep 3D Object Classification and Retrieval using Stereographic Projection
ํ์๋
ผ๋ฌธ(์์ฌ)--์์ธ๋ํ๊ต ๋ํ์ :๊ณต๊ณผ๋ํ ์ ๊ธฐยท์ปดํจํฐ๊ณตํ๋ถ,2019. 8. ์ด๊ฒฝ๋ฌด.๋ณธ ๋
ผ๋ฌธ์์๋ 3D ๋ฌผ์ฒด๋ถ๋ฅ ๋ฌธ์ ๋ฅผ ํจ์จ์ ์ผ๋ก ํด๊ฒฐํ๊ธฐ์ํ์ฌ ์
์ฒดํ๋ฒ์ ํฌ์ฌ๋ฅผ ํ์ฉํ ๋ชจ๋ธ์ ์ ์ํ๋ค. ๋จผ์ ์
์ฒดํ๋ฒ์ ํฌ์ฌ๋ฅผ ์ฌ์ฉํ์ฌ 3D ์
๋ ฅ ์์์ 2D ํ๋ฉด ์ด๋ฏธ์ง๋ก ๋ณํํ๋ค. ๋ํ, ๊ฐ์ฒด์ ์นดํ
๊ณ ๋ฆฌ๋ฅผ ์ถ์ ํ๊ธฐ ์ํ์ฌ ์์ 2Dํฉ์ฑ๊ณฑ์ ์
ฉ๋ง(CNN)์ ์ ์ํ๊ณ , ๋ค์ค์์ ์ผ๋ก๋ถํฐ ์ป์ ๊ฐ์ฒด ์นดํ
๊ณ ๋ฆฌ์ ์ถ์ ๊ฐ๋ค์ ๊ฒฐํฉํ์ฌ ์ฑ๋ฅ์ ๋์ฑ ํฅ์์ํค๋ ์์๋ธ ๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ์ด๋ฅผ์ํด (1) ์
์ฒดํ๋ฒํฌ์ฌ๋ฅผ ํ์ฉํ์ฌ 3D ๊ฐ์ฒด๋ฅผ 2D ํ๋ฉด ์ด๋ฏธ์ง๋ก ๋ณํํ๊ณ (2) ๋ค์ค์์ ์์๋ค์ ํน์ง์ ์ ํ์ต (3) ํจ๊ณผ์ ์ด๊ณ ๊ฐ์ธํ ์์ ์ ํน์ง์ ์ ์ ๋ณํ ํ (4) ๋ค์ค์์ ์์๋ธ์ ํตํ ์ฑ๋ฅ์ ํฅ์์ํค๋ 4๋จ๊ณ๋ก ๊ตฌ์ฑ๋ ํ์ต๋ฐฉ๋ฒ์ ์ ์ํ๋ค. ๋ณธ ๋
ผ๋ฌธ์์๋ ์คํ๊ฒฐ๊ณผ๋ฅผ ํตํด ์ ์ํ๋ ๋ฐฉ๋ฒ์ด ๋งค์ฐ ์ ์ ๋ชจ๋ธ์ ํ์ต ๋ณ์์ GPU ๋ฉ๋ชจ๋ฆฌ๋ฅผ ์ฌ์ฉํ๋๊ณผ ๋์์ ๊ฐ์ฒด ๋ถ๋ฅ ๋ฐ ๊ฒ์์์์ ์ฐ์ํ ์ฑ๋ฅ์ ๋ณด์ด๊ณ ์์์ ์ฆ๋ช
ํ์๋ค.We propose an efficient Stereographic Projection Neural Network (SPNet) for learning representations of 3D objects. We first transform a 3D input volume into a 2D planar image using stereographic projection. We then present a shallow 2D convolutional neural network (CNN) to estimate the object category followed by view ensemble, which combines the responses from multiple views of the object to further enhance the predictions. Specifically, the proposed approach consists of four stages: (1) Stereographic projection of a 3D object, (2) view-specific feature learning, (3) view selection and (4) view ensemble. The proposed approach performs comparably to the state-of-the-art methods while having substantially lower GPU memory as well as network parameters. Despite its lightness, the experiments on 3D object classification and shape retrievals demonstrate the high performance of the proposed method.1 INTRODUCTION
2 Related Work
2.1 Point cloud-based methods
2.2 3D model-based methods
2.3 2D/2.5D image-based methods
3 Proposed Stereographic Projection Network
3.1 Stereographic Representation
3.2 Network Architecture
3.3 View Selection
3.4 View Ensemble
4 Experimental Evaluation
4.1 Datasets
4.2 Training
4.3 Choice of Stereographic Projection
4.4 Test on View Selection Schemes
4.5 3D Object Classification
4.6 Shape Retrieval
4.7 Implementation
5 ConclusionsMaste
Charged Black Branes with Hyperscaling Violating Factor
We present an analytic solution of a charged black hole with hyperscaling
violating factor in an Einstein-Maxwell-Dilaton model where the scalar
potential is key to the existence of a solution. This solution provides a
candidate gravitational description of theories with hyperscaling violation at
both finite temperature and finite charge density. Using this background we
explore certain features of these theories via AdS/CFT correspondence. Finally,
we discuss embeddings based on the well-known sphere reductions of ten and
eleven-dimensional supergravity.Comment: 1+21 pages, section on optical conductivity added, references
corrected, agrees with published versio
ICF-SRSR: Invertible scale-Conditional Function for Self-Supervised Real-world Single Image Super-Resolution
Single image super-resolution (SISR) is a challenging ill-posed problem that
aims to up-sample a given low-resolution (LR) image to a high-resolution (HR)
counterpart. Due to the difficulty in obtaining real LR-HR training pairs,
recent approaches are trained on simulated LR images degraded by simplified
down-sampling operators, e.g., bicubic. Such an approach can be problematic in
practice because of the large gap between the synthesized and real-world LR
images. To alleviate the issue, we propose a novel Invertible scale-Conditional
Function (ICF), which can scale an input image and then restore the original
input with different scale conditions. By leveraging the proposed ICF, we
construct a novel self-supervised SISR framework (ICF-SRSR) to handle the
real-world SR task without using any paired/unpaired training data.
Furthermore, our ICF-SRSR can generate realistic and feasible LR-HR pairs,
which can make existing supervised SISR networks more robust. Extensive
experiments demonstrate the effectiveness of the proposed method in handling
SISR in a fully self-supervised manner. Our ICF-SRSR demonstrates superior
performance compared to the existing methods trained on synthetic paired images
in real-world scenarios and exhibits comparable performance compared to
state-of-the-art supervised/unsupervised methods on public benchmark datasets
ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion
Point cloud completion addresses filling in the missing parts of a partial
point cloud obtained from depth sensors and generating a complete point cloud.
Although there has been steep progress in the supervised methods on the
synthetic point cloud completion task, it is hardly applicable in real-world
scenarios due to the domain gap between the synthetic and real-world datasets
or the requirement of prior information. To overcome these limitations, we
propose a novel self-supervised framework ACL-SPC for point cloud completion to
train and test on the same data. ACL-SPC takes a single partial input and
attempts to output the complete point cloud using an adaptive closed-loop (ACL)
system that enforces the output same for the variation of an input. We evaluate
our proposed ACL-SPC on various datasets to prove that it can successfully
learn to complete a partial point cloud as the first self-supervised scheme.
Results show that our method is comparable with unsupervised methods and
achieves superior performance on the real-world dataset compared to the
supervised methods trained on the synthetic dataset. Extensive experiments
justify the necessity of self-supervised learning and the effectiveness of our
proposed method for the real-world point cloud completion task. The code is
publicly available from https://github.com/Sangminhong/ACL-SPC_PyTorchComment: Published at CVPR 202
Supergravity Description of the Large N Noncommutative Dipole Field Theories
We consider system of Dp-branes in the presence of a nonzero B field with one
leg along brane worldvolume and the other transverse to it. We study the
corresponding supergravity solutions and show that the worldvolume theories
decouple from gravity for . Therefore these solutions provide dual
description of large N noncommutative dipole field theories. We shall only
consider those systems which preserve 8 supercharges in the branes worldvolume.
We analyze the system of M5-branes and NS5-branes in the presence of nonzero C
field and RR field with one leg along the transverse direction and the others
along the worldvolume of the brane, respectively. This could provide a new
deformation of (2,0) and little string field theories. Finally, we study the
Wilson loops using the dual gravity descriptions.Comment: 24 pages, Latex fil
On Supergravity Solutions of Branes in Melvin Universes
We study supergravity solutions of type II branes wrapping a Melvin universe.
These solutions provide the gravity description of non-commutative field
theories with non-constant non-commutative parameter. Typically these theories
are non-supersymmetric, though they exhibit some feature of their corresponding
supersymmetric theories. An interesting feature of these non-commutative
theories is that there is a critical length in the theory in which for
distances larger than this length the effects of non-commutativity become
important and for smaller distances these effects are negligible. Therefore we
would expect to see this kind of non-commutativity in large distances which
might be relevant in cosmology. We also study M5-brane wrapping on
11-dimensional Melvin universe and its descendant theories upon compactifying
on a circle.Comment: 25 pages, latex file; v2: typos corrected, Refs. adde
Multi-spin string solutions in AdS Black Hole and confining backgrounds
We study semi-classical multi-spin strings in the non-supersymmetric
backgrounds of Black Hole and Witten's confining model. We consider
constant radius strings with rotations along the isometries of the backgrounds.
In the Black Hole, solutions exist only if there is a non-zero spin in
the Black Hole part. In contrast with the background, we find solutions
which although have no rotation in the part, have a regular
expansion in the expression for large energy. In the near-extremal and
backgrounds, we find that strings have to be located on the confining
wall. We also discuss the stability of solutions by considering the fluctuation
Lagrangians.Comment: 26 pages, LaTeX, references adde