Search Results for author: Zhiying Jiang

Found 23 papers, 8 papers with code

Towards Robust Image Stitching: An Adaptive Resistance Learning against Compatible Attacks

1 code implementation25 Feb 2024 Zhiying Jiang, Xingyuan Li, JinYuan Liu, Xin Fan, Risheng Liu

Given a pair of captured images, subtle perturbations and distortions which go unnoticed by the human visual system tend to attack the correspondence matching, impairing the performance of image stitching algorithms.

Image Stitching

From Text to Pixels: A Context-Aware Semantic Synergy Solution for Infrared and Visible Image Fusion

no code implementations31 Dec 2023 Xingyuan Li, Yang Zou, JinYuan Liu, Zhiying Jiang, Long Ma, Xin Fan, Risheng Liu

With the rapid progression of deep learning technologies, multi-modality image fusion has become increasingly prevalent in object detection tasks.

Bilevel Optimization Infrared And Visible Image Fusion +2

Holistic Dynamic Frequency Transformer for Image Fusion and Exposure Correction

no code implementations3 Sep 2023 Xiaoke Shang, Gehui Li, Zhiying Jiang, Shaomin Zhang, Nai Ding, JinYuan Liu

The correction of exposure-related issues is a pivotal component in enhancing the quality of images, offering substantial implications for various computer vision tasks.

Benchmarking Image Restoration

Fearless Luminance Adaptation: A Macro-Micro-Hierarchical Transformer for Exposure Correction

no code implementations2 Sep 2023 Gehui Li, JinYuan Liu, Long Ma, Zhiying Jiang, Xin Fan, Risheng Liu

To overcome these limitations, we propose a Macro-Micro-Hierarchical transformer, which consists of a macro attention to capture long-range dependencies, a micro attention to extract local features, and a hierarchical structure for coarse-to-fine correction.

Face Recognition Semantic Segmentation

Approximating Human-Like Few-shot Learning with GPT-based Compression

no code implementations14 Aug 2023 Cynthia Huang, Yuqing Xie, Zhiying Jiang, Jimmy Lin, Ming Li

Leveraging the approximated information distance, our method allows the direct application of GPT models in quantitative text similarity measurements.

Data Compression Few-Shot Learning +6

WaterFlow: Heuristic Normalizing Flow for Underwater Image Enhancement and Beyond

no code implementations2 Aug 2023 Zengxi Zhang, Zhiying Jiang, JinYuan Liu, Xin Fan, Risheng Liu

Underwater images suffer from light refraction and absorption, which impairs visibility and interferes the subsequent applications.

Image Enhancement

Multi-Spectral Image Stitching via Spatial Graph Reasoning

no code implementations31 Jul 2023 Zhiying Jiang, Zengxi Zhang, JinYuan Liu, Xin Fan, Risheng Liu

Multi-spectral image stitching leverages the complementarity between infrared and visible images to generate a robust and reliable wide field-of-view (FOV) scene.

Image Stitching

Contrastive Learning Based Recursive Dynamic Multi-Scale Network for Image Deraining

no code implementations29 May 2023 Zhiying Jiang, Risheng Liu, Shuzhou Yang, Zengxi Zhang, Xin Fan

Extensive experiments on synthetic benchmarks and real-world images demonstrate that the proposed RDMC delivers strong performance on the depiction of rain streaks and outperforms the state-of-the-art methods.

Contrastive Learning object-detection +3

Breaking Modality Disparity: Harmonized Representation for Infrared and Visible Image Registration

no code implementations12 Apr 2023 Zhiying Jiang, Zengxi Zhang, JinYuan Liu, Xin Fan, Risheng Liu

Since the differences in viewing range, resolution and relative position, the multi-modality sensing module composed of infrared and visible cameras needs to be registered so as to have more accurate scene perception.

Image Registration

A Theory of Human-Like Few-Shot Learning

no code implementations3 Jan 2023 Zhiying Jiang, Rui Wang, Dongbo Bu, Ming Li

We aim to bridge the gap between our common-sense few-sample human learning and large-data machine learning.

Common Sense Reasoning Few-Shot Learning

Less is More: Parameter-Free Text Classification with Gzip

no code implementations19 Dec 2022 Zhiying Jiang, Matthew Y. R. Yang, Mikhail Tsirlin, Raphael Tang, Jimmy Lin

Our method also performs particularly well in few-shot settings where labeled data are too scarce for DNNs to achieve a satisfying accuracy.

text-classification Text Classification

What the DAAM: Interpreting Stable Diffusion Using Cross Attention

1 code implementation10 Oct 2022 Raphael Tang, Linqing Liu, Akshat Pandey, Zhiying Jiang, Gefei Yang, Karun Kumar, Pontus Stenetorp, Jimmy Lin, Ferhan Ture

Large-scale diffusion neural networks represent a substantial milestone in text-to-image generation, but they remain poorly understood, lacking interpretability analyses.

Denoising Descriptive +3

Building an Efficiency Pipeline: Commutativity and Cumulativeness of Efficiency Operators for Transformers

no code implementations31 Jul 2022 Ji Xin, Raphael Tang, Zhiying Jiang, YaoLiang Yu, Jimmy Lin

There exists a wide variety of efficiency methods for natural language processing (NLP) tasks, such as pruning, distillation, dynamic inference, quantization, etc.


Few-Shot Non-Parametric Learning with Deep Latent Variable Model

no code implementations23 Jun 2022 Zhiying Jiang, Yiqin Dai, Ji Xin, Ming Li, Jimmy Lin

Most real-world problems that machine learning algorithms are expected to solve face the situation with 1) unknown data distribution; 2) little domain-specific knowledge; and 3) datasets with limited annotation.

Classification Image Classification

Investigating the Limitations of Transformers with Simple Arithmetic Tasks

1 code implementation25 Feb 2021 Rodrigo Nogueira, Zhiying Jiang, Jimmy Lin

In this work, we investigate if the surface form of a number has any influence on how sequence-to-sequence language models learn simple arithmetic tasks such as addition and subtraction across a wide range of values.

Inserting Information Bottlenecks for Attribution in Transformers

1 code implementation Findings of the Association for Computational Linguistics 2020 Zhiying Jiang, Raphael Tang, Ji Xin, Jimmy Lin

We show the effectiveness of our method in terms of attribution and the ability to provide insight into how information flows through layers.

Navigation-Based Candidate Expansion and Pretrained Language Models for Citation Recommendation

no code implementations23 Jan 2020 Rodrigo Nogueira, Zhiying Jiang, Kyunghyun Cho, Jimmy Lin

Citation recommendation systems for the scientific literature, to help authors find papers that should be cited, have the potential to speed up discoveries and uncover new routes for scientific exploration.

Citation Recommendation Domain Adaptation +3

PaperRobot: Incremental Draft Generation of Scientific Ideas

2 code implementations ACL 2019 Qingyun Wang, Lifu Huang, Zhiying Jiang, Kevin Knight, Heng Ji, Mohit Bansal, Yi Luan

We present a PaperRobot who performs as an automatic research assistant by (1) conducting deep understanding of a large collection of human-written papers in a target domain and constructing comprehensive background knowledge graphs (KGs); (2) creating new ideas by predicting links from the background KGs, by combining graph attention and contextual text attention; (3) incrementally writing some key elements of a new paper based on memory-attention networks: from the input title along with predicted related entities to generate a paper abstract, from the abstract to generate conclusion and future work, and finally from future work to generate a title for a follow-on paper.

Graph Attention Knowledge Graphs +4

Chengyu Cloze Test

1 code implementation WS 2018 Zhiying Jiang, Boliang Zhang, Lifu Huang, Heng Ji

We present a neural recommendation model for Chengyu, which is a special type of Chinese idiom.

Cloze Test Sentence

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