An attention-based hybrid deep learning approach for bengali video captioning

Article Computer Science, Artificial Intelligence

An attention based dual learning approach for video captioning

Wanting Ji et al.

Summary: Video captioning is an important task in multimedia processing, and traditional approaches only utilize visual information to generate captions. This paper proposes a novel attention based dual learning approach (ADL) that improves the quality of video captions by minimizing the differences between generated and raw videos.

APPLIED SOFT COMPUTING (2022)

添加到收藏夹

Article Computer Science, Information Systems

Robust regularization for single image dehazing

Usman Ali et al.

Summary: This paper proposes an improved image dehazing method by optimizing a nonconvex energy function that leverages structural information from the transmission map and guidance. The proposed method provides robust regularization and achieves high-quality haze-free images.

JOURNAL OF KING SAUD UNIVERSITY-COMPUTER AND INFORMATION SCIENCES (2022)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

SWINBERT: End-to-End Transformers with Sparse Attention for Video Captioning

Kevin Lin et al.

Summary: This paper presents SWINBERT, an end-to-end transformer-based model for video captioning, which directly takes video frame patches as inputs and outputs natural language descriptions. It shows that video captioning can benefit significantly from more densely sampled video frames and proposes adaptively learning a sparse attention mask for better long-range video sequence modeling. Extensive experiments demonstrate the performance improvements of SWINBERT over previous methods and the effectiveness of the learned attention masks.

2022 IEEE/CVF CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2022) (2022)

添加到收藏夹

Article Computer Science, Artificial Intelligence

Towards achieving a delicate blending between rule-based translator and neural machine translator

Md Adnanul Islam et al.

Summary: Popular translators excel in translating among high-resource languages but may make mistakes when translating low-resource languages. The study aims to improve translation from Bengali to English by exploring different blending approaches. Rigorous experimentation is conducted to compare the performance of different translation approaches.

NEURAL COMPUTING & APPLICATIONS (2021)

添加到收藏夹

Article Computer Science, Artificial Intelligence