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Language-Driven Region Pointer Advancement for Controllable Image Captioning
AnnikaLindh, RobertJ.Ross, JohnD.Kelleher....
Published date-11/30/2020
ImageCaptioning
Controllable Image Captioning is a recent sub-field in the multi-modal task of Image Captioning wherein constraints are placed on which regions in an image should be described in the generated …
Move to See Better: Towards Self-Supervised Amodal Object Detection
ZhaoyuanFang, AyushJain, GabrielSarch....
Published date-11/30/2020
ObjectDetection
Humans learn to better understand the world by moving around their environment to get more informative viewpoints of the scene. Most methods for 2D visual recognition tasks such as object …
UWB @ DIACR-Ita: Lexical Semantic Change Detection with CCA and Orthogonal Transformation
OndřejPražák, PavelPřibáň, StephenTaylor....
Published date-11/30/2020
In this paper, we describe our method for detection of lexical semantic change (i.e., word sense changes over time) for the DIACR-Ita shared task, where we ranked $1^{st}$. We examine …
FCM-RDpA: TSK Fuzzy Regression Model Construction Using Fuzzy C-Means Clustering, Regularization, DropRule, and Powerball AdaBelief
ZhenhuaShi, DongruiWu, ChenfengGuo....
Published date-11/30/2020
Clustering
To effectively optimize Takagi-Sugeno-Kang (TSK) fuzzy systems for regression problems, a mini-batch gradient descent with regularization, DropRule, and AdaBound (MBGD-RDA) algorithm was recently proposed. This paper further proposes FCM-RDpA, which …
SplitNet: Divide and Co-training
ShuaiZhao, LiguangZhou, WenxiaoWang....
Published date-11/30/2020
ImageClassification
The width of a neural network matters since increasing the width will necessarily increase the model capacity. However, the performance of a network does not improve linearly with the width …
Large-Scale Gravitational Lens Modeling with Bayesian Neural Networks for Accurate and Precise Inference of the Hubble Constant
JiWonPark, SebastianWagner-Carena, SimonBirrer....
Published date-11/30/2020
We investigate the use of approximate Bayesian neural networks (BNNs) in modeling hundreds of time-delay gravitational lenses for Hubble constant ($H_0$) determination. Our BNN was trained on synthetic HST-quality images …