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06/19/2023
UncLe-SLAM: Uncertainty Learning for Dense Neural SLAM
We present an uncertainty learning framework for dense neural simultaneo...
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05/19/2023
Equivariant Multi-Modality Image Fusion
Multi-modality image fusion is a technique used to combine information f...
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04/27/2023
Neural Implicit Dense Semantic SLAM
This paper presents an efficient online framework to solve the well-know...
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04/21/2023
Advances in Deep Concealed Scene Understanding
Concealed scene understanding (CSU) is a hot computer vision topic aimin...
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03/31/2023
Single Image Depth Prediction Made Better: A Multivariate Gaussian Take
Neural-network-based single image depth prediction (SIDP) is a challengi...
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03/15/2023
Spherical Space Feature Decomposition for Guided Depth Map Super-Resolution
Guided depth map super-resolution (GDSR), as a hot topic in multi-modal ...
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03/01/2023
Efficient and Explicit Modelling of Image Hierarchies for Image Restoration
The aim of this paper is to propose a mechanism to efficiently and expli...
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01/12/2023
Event-Based Frame Interpolation with Ad-hoc Deblurring
The performance of video frame interpolation is inherently correlated wi...
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11/26/2022
CDDFuse: Correlation-Driven Dual-Branch Feature Decomposition for Multi-Modality Image Fusion
Multi-modality (MM) image fusion aims to render fused images that mainta...
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11/13/2022
Advancing Learned Video Compression with In-loop Frame Prediction
Recent years have witnessed an increasing interest in end-to-end learned...
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10/28/2022
TripletTrack: 3D Object Tracking using Triplet Embeddings and LSTM
3D object tracking is a critical task in autonomous driving systems. It ...
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06/29/2022
3D-Aware Video Generation
Generative models have emerged as an essential building block for many i...
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05/25/2022
Deep Gradient Learning for Efficient Camouflaged Object Detection
This paper introduces DGNet, a novel deep framework that exploits object...
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04/27/2022
HRDA: Context-Aware High-Resolution Domain-Adaptive Semantic Segmentation
Unsupervised domain adaptation (UDA) aims to adapt a model trained on th...
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04/13/2022
Neural Vector Fields for Surface Representation and Inference
Neural implicit fields have recently been shown to represent 3D shapes a...
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04/04/2022
Direct Dense Pose Estimation
Dense human pose estimation is the problem of learning dense corresponde...
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03/20/2022
Transform your Smartphone into a DSLR Camera: Learning the ISP in the Wild
We propose a trainable Image Signal Processing (ISP) framework that prod...
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03/07/2022
ZippyPoint: Fast Interest Point Detection, Description, and Matching through Mixed Precision Discretization
The design of more complex and powerful neural network models has signif...
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02/26/2022
Uncertainty-Aware Deep Multi-View Photometric Stereo
This paper presents a simple and effective solution to the problem of mu...
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01/28/2022
VRT: A Video Restoration Transformer
Video restoration (e.g., video super-resolution) aims to restore high-qu...
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01/24/2022
RePaint: Inpainting using Denoising Diffusion Probabilistic Models
Free-form inpainting is the task of adding new content to an image in th...
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01/17/2022
Collapse by Conditioning: Training Class-conditional GANs with Limited Data
Class-conditioning offers a direct means of controlling a Generative Adv...
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12/17/2021
Efficient Visual Tracking with Exemplar Transformers
The design of more complex and powerful neural network models has signif...
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12/08/2021
Implicit Neural Representations for Image Compression
Recently Implicit Neural Representations (INRs) gained attention as a no...
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11/29/2021
DAFormer: Improving Network Architectures and Training Strategies for Domain-Adaptive Semantic Segmentation
As acquiring pixel-wise annotations of real-world images for semantic se...
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11/24/2021
MHFormer: Multi-Hypothesis Transformer for 3D Human Pose Estimation
Estimating 3D human poses from monocular videos is a challenging task du...
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11/15/2021
Mask-guided Spectral-wise Transformer for Efficient Hyperspectral Image Reconstruction
Hyperspectral image (HSI) reconstruction aims to recover the 3D spatial-...
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09/28/2021
PDC-Net+: Enhanced Probabilistic Dense Correspondence Network
Establishing robust and accurate correspondences between a pair of image...
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09/16/2021
Context-aware Padding for Semantic Segmentation
Zero padding is widely used in convolutional neural networks to prevent ...
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09/07/2021
Perceptual Learned Video Compression with Recurrent Conditional GAN
This paper proposes a Perceptual Learned Video Compression (PLVC) approa...
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08/23/2021
SwinIR: Image Restoration Using Swin Transformer
Image restoration is a long-standing low-level vision problem that aims ...
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08/18/2021
Deep Reparametrization of Multi-Frame Super-Resolution and Denoising
We propose a deep reparametrization of the maximum a posteriori formulat...
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07/02/2021
A Survey on Deep Learning Technique for Video Segmentation
Video segmentation, i.e., partitioning video frames into multiple segmen...
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06/12/2021
Video Super-Resolution Transformer
Video super-resolution (VSR), with the aim to restore a high-resolution ...
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06/07/2021
Generative Flows with Invertible Attentions
Flow-based generative models have shown excellent ability to explicitly ...
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01/26/2021
Deep Burst Super-Resolution
While single-image super-resolution (SISR) has attracted substantial int...
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01/17/2021
Trilevel Neural Architecture Search for Efficient Single Image Super-Resolution
This paper proposes a trilevel neural architecture search (NAS) method f...
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12/05/2020
Quantifying Aleatoric and Epistemic Uncertainty Using Density Estimation in Latent Space
The distribution of a neural network's latent representations has been s...
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10/22/2020
Self-Supervised Shadow Removal
Shadow removal is an important computer vision task aiming at the detect...
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06/29/2020
OpenDVC: An Open Source Implementation of the DVC Video Compression Method
We introduce an open source Tensorflow implementation of the Deep Video ...
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06/24/2020
Learning for Video Compression with Recurrent Auto-Encoder and Recurrent Probability Model
The past few years have witnessed increasing interests in applying deep ...
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06/15/2020
Dense Non-Rigid Structure from Motion: A Manifold Viewpoint
Non-Rigid Structure-from-Motion (NRSfM) problem aims to recover 3D geome...
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05/25/2020
Learning To Classify Images Without Labels
Is it possible to automatically classify images without the use of groun...
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04/28/2020
Revisiting Multi-Task Learning in the Deep Learning Era
Despite the recent progress in deep learning, most approaches still go f...
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04/03/2020
Quantifying Data Augmentation for LiDAR based 3D Object Detection
In this work, we shed light on different data augmentation techniques co...
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03/30/2020
DHP: Differentiable Meta Pruning via HyperNetworks
Network pruning has been the driving force for the efficient inference o...
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03/19/2020
Group Sparsity: The Hinge Between Filter Pruning and Decomposition for Network Compression
In this paper, we analyze two popular network compression techniques, i....
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02/13/2020
Replacing Mobile Camera ISP with a Single Deep Learning Model
As the popularity of mobile photography is growing constantly, lots of e...
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12/09/2019
Self-supervised Object Motion and Depth Estimation from Video
We present a self-supervised learning framework to estimate the individu...
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06/03/2019
