NTIRE 2024 image shadow removal challenge report
This work reviews the results of the NTIRE 2024 Challenge on Shadow Removal. Building
on the last year edition the current challenge was organized in two tracks with a track …
on the last year edition the current challenge was organized in two tracks with a track …
A hybrid video anomaly detection framework via memory-augmented flow reconstruction and flow-guided frame prediction
In this paper, we propose HF2-VAD, a Hybrid framework that integrates Flow reconstruction
and Frame prediction seamlessly to handle Video Anomaly Detection. Firstly, we design the …
and Frame prediction seamlessly to handle Video Anomaly Detection. Firstly, we design the …
Spatially-adaptive image restoration using distortion-guided networks
We present a general learning-based solution for restoring images suffering from spatially-
varying degradations. Prior approaches are typically degradation-specific and employ the …
varying degradations. Prior approaches are typically degradation-specific and employ the …
Canet: A context-aware network for shadow removal
Z Chen, C Long, L Zhang… - Proceedings of the IEEE …, 2021 - openaccess.thecvf.com
In this paper, we propose a novel two-stage context-aware network named CANet for
shadow removal, in which the contextual information from non-shadow regions is transferred …
shadow removal, in which the contextual information from non-shadow regions is transferred …
Drb-gan: A dynamic resblock generative adversarial network for artistic style transfer
In this work, we propose a Dynamic ResBlock Generative Adversarial Network (DRB-GAN)
for artistic style transfer. The style code is modeled as the shared parameters for Dynamic …
for artistic style transfer. The style code is modeled as the shared parameters for Dynamic …
Residual denoising diffusion models
We propose residual denoising diffusion models (RDDM) a novel dual diffusion process that
decouples the traditional single denoising diffusion process into residual diffusion and noise …
decouples the traditional single denoising diffusion process into residual diffusion and noise …
From shadow segmentation to shadow removal
The requirement for paired shadow and shadow-free images limits the size and diversity of
shadow removal datasets and hinders the possibility of training large-scale, robust shadow …
shadow removal datasets and hinders the possibility of training large-scale, robust shadow …
DOA-GAN: Dual-order attentive generative adversarial network for image copy-move forgery detection and localization
Images can be manipulated for nefarious purposes to hide content or to duplicate certain
objects through copy-move operations. Discovering a well-crafted copy-move forgery in …
objects through copy-move operations. Discovering a well-crafted copy-move forgery in …
Single-image shadow removal using deep learning: A comprehensive survey
Shadow removal aims at restoring the image content within shadow regions, pursuing a
uniform distribution of illumination that is consistent between shadow and non-shadow …
uniform distribution of illumination that is consistent between shadow and non-shadow …
Arshadowgan: Shadow generative adversarial network for augmented reality in single light scenes
D Liu, C Long, H Zhang, H Yu… - Proceedings of the …, 2020 - openaccess.thecvf.com
Generating virtual object shadows consistent with the real-world environment shading
effects is important but challenging in computer vision and augmented reality applications …
effects is important but challenging in computer vision and augmented reality applications …