1.1k citations · 1.6k across the 68 of their papers we have counts for
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LLDiffusion: Learning Degradation Representations in Diffusion Models for Low-Light Image Enhancement
Tao Wang, Kaihao Zhang, Ziqian Shao +5
Current deep learning methods for low-light image enhancement (LLIE) typically rely on pixel-wise mapping learned from paired data. However, these methods often overlook the import…
FourierHandFlow: Neural 4D Hand Representation Using Fourier Query Flow
Jihyun Lee, Junbong Jang, Donghwan Kim +2
Recent 4D shape representations model continuous temporal evolution of implicit shapes by (1) learning query flows without leveraging shape and articulation priors or (2) decoding…
iEdit: Localised Text-guided Image Editing with Weak Supervision
Rumeysa Bodur, Erhan Gundogdu, Binod Bhattarai +3
Diffusion models (DMs) can generate realistic images with text guidance using large-scale datasets. However, they demonstrate limited controllability in the output space of the gen…
PoseMatcher: One-shot 6D Object Pose Estimation by Deep Feature Matching
Pedro Castro, Tae-Kyun Kim
Estimating the pose of an unseen object is the goal of the challenging one-shot pose estimation task. Previous methods have heavily relied on feature matching with great success. H…
MAPConNet: Self-supervised 3D Pose Transfer with Mesh and Point Contrastive Learning
Jiaze Sun, Zhixiang Chen, Tae-Kyun Kim
3D pose transfer is a challenging generation task that aims to transfer the pose of a source geometry onto a target geometry with the target identity preserved. Many prior methods…
Im2Hands: Learning Attentive Implicit Representation of Interacting Two-Hand Shapes
Jihyun Lee, Minhyuk Sung, Honggyu Choi +1
We present Implicit Two Hands (Im2Hands), the first neural implicit representation of two interacting hands. Unlike existing methods on two-hand reconstruction that rely on a param…
Unsupervised Contour Tracking of Live Cells by Mechanical and Cycle Consistency Losses
Junbong Jang, Kwonmoo Lee, Tae-Kyun Kim
Analyzing the dynamic changes of cellular morphology is important for understanding the various functions and characteristics of live cells, including stem cells and metastatic can…
MoBYv2AL: Self-supervised Active Learning for Image Classification
Razvan Caramalau, Binod Bhattarai, Danail Stoyanov +1
Active learning(AL) has recently gained popularity for deep learning(DL) models. This is due to efficient and informative sampling, especially when the learner requires large-scale…
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…
A Unified Architecture of Semantic Segmentation and Hierarchical Generative Adversarial Networks for Expression Manipulation
Rumeysa Bodur, Binod Bhattarai, Tae-Kyun Kim
Editing facial expressions by only changing what we want is a long-standing research problem in Generative Adversarial Networks (GANs) for image manipulation. Most of the existing…
EvDistill: Asynchronous Events to End-task Learning via Bidirectional Reconstruction-guided Cross-modal Knowledge Distillation
Lin Wang, Yujeong Chae, Sung-Hoon Yoon +2
Event cameras sense per-pixel intensity changes and produce asynchronous event streams with high dynamic range and less motion blur, showing advantages over conventional cameras. A…
SeCGAN: Parallel Conditional Generative Adversarial Networks for Face Editing via Semantic Consistency
Jiaze Sun, Binod Bhattarai, Zhixiang Chen +1
Semantically guided conditional Generative Adversarial Networks (cGANs) have become a popular approach for face editing in recent years. However, most existing methods introduce se…
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…
Geometry-based Distance Decomposition for Monocular 3D Object Detection
Xuepeng Shi, Qi Ye, Xiaozhi Chen +3
Monocular 3D object detection is of great significance for autonomous driving but remains challenging. The core challenge is to predict the distance of objects in the absence of ex…
Active Learning for Bayesian 3D Hand Pose Estimation
Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim
We propose a Bayesian approximation to a deep learning architecture for 3D hand pose estimation. Through this framework, we explore and analyse the two types of uncertainties that…
3D Dense Geometry-Guided Facial Expression Synthesis by Adversarial Learning
Rumeysa Bodur, Binod Bhattarai, Tae-Kyun Kim
Manipulating facial expressions is a challenging task due to fine-grained shape changes produced by facial muscles and the lack of input-output pairs for supervised learning. Unlik…
Physics-Based Dexterous Manipulations with Estimated Hand Poses and Residual Reinforcement Learning
Guillermo Garcia-Hernando, Edward Johns, Tae-Kyun Kim
Dexterous manipulation of objects in virtual environments with our bare hands, by using only a depth sensor and a state-of-the-art 3D hand pose estimator (HPE), is challenging. Whi…
Sequential Graph Convolutional Network for Active Learning
Razvan Caramalau, Binod Bhattarai, Tae-Kyun Kim
We propose a novel pool-based Active Learning framework constructed on a sequential Graph Convolution Network (GCN). Each image's feature from a pool of data represents a node in t…
MatchGAN: A Self-Supervised Semi-Supervised Conditional Generative Adversarial Network
Jiaze Sun, Binod Bhattarai, Tae-Kyun Kim
We present a novel self-supervised learning approach for conditional generative adversarial networks (GANs) under a semi-supervised setting. Unlike prior self-supervised approaches…
Additive Angular Margin for Few Shot Learning to Classify Clinical Endoscopy Images
Sharib Ali, Binod Bhattarai, Tae-Kyun Kim +1
Endoscopy is a widely used imaging modality to diagnose and treat diseases in hollow organs as for example the gastrointestinal tract, the kidney and the liver. However, due to var…