This paper presents a novel network structure with illumination-aware ga...
Event-based motion deblurring has shown promising results by exploiting
...
Recently, semantic segmentation models trained with image-level text
sup...
The stereo event-intensity camera setup is widely applied to leverage th...
Latest diffusion-based methods for many image restoration tasks outperfo...
Continual learning aims to enable a model to incrementally learn knowled...
Pre-trained vision-language models have inspired much research on few-sh...
Brain signal visualization has emerged as an active research area, servi...
In recent years, videos and images in 720p (HD), 1080p (FHD) and 4K (UHD...
Medical artificial general intelligence (MAGI) enables one foundation mo...
Face animation has achieved much progress in computer vision. However,
p...
This paper aims at demystifying a single motion-blurred image with event...
Image super-resolution (SR) has attracted increasing attention due to it...
Super-Resolution from a single motion Blurred image (SRB) is a severely
...
Vision-Language Navigation (VLN) is a challenging task which requires an...
Pedestrian detection in the wild remains a challenging problem especiall...
Referring image segmentation aims at localizing all pixels of the visual...
Face animation, one of the hottest topics in computer vision, has achiev...
Though graph representation learning (GRL) has made significant progress...
Due to the difficulty in collecting paired real-world training data, ima...
Humans can continuously learn new knowledge. However, machine learning m...
Low-light video enhancement (LLVE) is an important yet challenging task ...
Top-down methods dominate the field of 3D human pose and shape estimatio...
Existing few-shot learning (FSL) methods rely on training with a large
l...
Vision-Language Navigation (VLN) is a challenging task that requires an
...
As an inherently ill-posed problem, depth estimation from single images ...
We present prompt distribution learning for effectively adapting a
pre-t...
Color constancy aims to restore the constant colors of a scene under
dif...
Referring expression comprehension (REC) aims to locate a certain object...
We propose a novel zero-shot multi-frame image restoration method for
re...
Learning to synthesize data has emerged as a promising direction in zero...
In this paper, we propose an end-to-end learning framework for event-bas...
A resource-adaptive supernet adjusts its subnets for inference to fit th...
High dynamic range (HDR) imaging from multiple low dynamic range (LDR) i...
The mainstream approach for filter pruning is usually either to force a
...
Recently unsupervised domain adaptation for the semantic segmentation ta...
In this paper, we present Uformer, an effective and efficient
Transforme...
Channel pruning and tensor decomposition have received extensive attenti...
Despite the substantial progress of active learning for image recognitio...
Binary neural networks (BNNs) have received increasing attention due to ...
Multi-source unsupervised domain adaptation (MSDA) aims at adapting mode...
Data-driven based approaches, in spite of great success in many tasks, h...
In the last few years, image denoising has benefited a lot from the fast...
Moire artifacts are common in digital photography, resulting from the
in...
Traditional neural architecture search (NAS) has a significant impact in...
This paper presents a learning-based approach to synthesize the view fro...
Domain generalization (DG) serves as a promising solution to handle pers...
When smartphone cameras are used to take photos of digital screens, usua...
Generating adversarial examples in a black-box setting retains a signifi...
Plenoptic cameras usually sacrifice the spatial resolution of their SAIs...