49 citations · 116 across the 14 of their papers we have counts for
38 papers
Semi-Supervised Object Detection with Object-wise Contrastive Learning and Regression Uncertainty
Honggyu Choi, Zhixiang Chen, Xuepeng Shi +1
Semi-supervised object detection (SSOD) aims to boost detection performance by leveraging extra unlabeled data. The teacher-student framework has been shown to be promising for SSO…
CRT-6D: Fast 6D Object Pose Estimation with Cascaded Refinement Transformers
Pedro Castro, Tae-Kyun Kim
Learning based 6D object pose estimation methods rely on computing large intermediate pose representations and/or iteratively refining an initial estimation with a slow render-comp…
Pop-Out Motion: 3D-Aware Image Deformation via Learning the Shape Laplacian
Jihyun Lee, Minhyuk Sung, Hyunjin Kim +1
We propose a framework that can deform an object in a 2D image as it exists in 3D space. Most existing methods for 3D-aware image manipulation are limited to (1) only changing the…
Visual Transformer for Task-aware Active Learning
Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim
Pool-based sampling in active learning (AL) represents a key framework for an-notating informative data when dealing with deep learning models. In this paper, we present a novel pi…
Label Geometry Aware Discriminator for Conditional Generative Networks
Suman Sapkota, Bidur Khanal, Binod Bhattarai +2
Multi-domain image-to-image translation with conditional Generative Adversarial Networks (GANs) can generate highly photo realistic images with desired target classes, yet these sy…
Learning Feature Aggregation for Deep 3D Morphable Models
Zhixiang Chen, Tae-Kyun Kim
3D morphable models are widely used for the shape representation of an object class in computer vision and graphics applications. In this work, we focus on deep 3D morphable models…