NTIRE 2023 challenge on efficient super-resolution: Methods and results
This paper reviews the NTIRE 2023 challenge on efficient single-image super-resolution
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
with a focus on the proposed solutions and results. The aim of this challenge is to devise a …
YOLOv7: Trainable bag-of-freebies sets new state-of-the-art for real-time object detectors
Real-time object detection is one of the most important research topics in computer vision.
As new approaches regarding architecture optimization and training optimization are …
As new approaches regarding architecture optimization and training optimization are …
3d ux-net: A large kernel volumetric convnet modernizing hierarchical transformer for medical image segmentation
The recent 3D medical ViTs (eg, SwinUNETR) achieve the state-of-the-art performances on
several 3D volumetric data benchmarks, including 3D medical image segmentation …
several 3D volumetric data benchmarks, including 3D medical image segmentation …
Make repvgg greater again: A quantization-aware approach
The tradeoff between performance and inference speed is critical for practical applications.
Architecture reparameterization obtains better tradeoffs and it is becoming an increasingly …
Architecture reparameterization obtains better tradeoffs and it is becoming an increasingly …
Efficient deep models for real-time 4k image super-resolution. NTIRE 2023 benchmark and report
This paper introduces a novel benchmark for efficient upscaling as part of the NTIRE 2023
Real-Time Image Super-Resolution (RTSR) Challenge, which aimed to upscale images …
Real-Time Image Super-Resolution (RTSR) Challenge, which aimed to upscale images …
You only look once-object detection models: a review
A Nazir, MA Wani - 2023 10th International Conference on …, 2023 - ieeexplore.ieee.org
Object detection is the task of detecting instances of particular classes in an image. The You
Only Look Once (YOLO) object detection algorithms have become popular in recent years …
Only Look Once (YOLO) object detection algorithms have become popular in recent years …
Mi-gan: A simple baseline for image inpainting on mobile devices
In recent years, many deep learning based image inpainting methods have been developed
by the research community. Some of those methods have shown impressive image …
by the research community. Some of those methods have shown impressive image …
YOLO-FA: Type-1 fuzzy attention based YOLO detector for vehicle detection
L Kang, Z Lu, L Meng, Z Gao - Expert Systems with Applications, 2024 - Elsevier
Vehicle detection is an important component of intelligent transportation systems and
autonomous driving. However, in real-world vehicle detection scenarios, the presence of …
autonomous driving. However, in real-world vehicle detection scenarios, the presence of …
Lighting every darkness in two pairs: A calibration-free pipeline for raw denoising
Calibration-based methods have dominated RAW image denoising under extremely low-
light environments. However, these methods suffer from several main deficiencies: 1) the …
light environments. However, these methods suffer from several main deficiencies: 1) the …
YOLOPX: Anchor-free multi-task learning network for panoptic driving perception
J Zhan, Y Luo, C Guo, Y Wu, J Meng, J Liu - Pattern Recognition, 2024 - Elsevier
Panoptic driving perception encompasses traffic object detection, drivable area
segmentation, and lane detection. Existing methods typically utilize anchor-based multi-task …
segmentation, and lane detection. Existing methods typically utilize anchor-based multi-task …