2 code implementations • 9 Apr 2024 • Pan Mu, Zhiying Du, JinYuan Liu, Cong Bai
In recent years, deep learning networks have made remarkable strides in the domain of multi-exposure image fusion.
1 code implementation • ACMMM 2023 • Jiancheng Pan, Qing Ma, Cong Bai
Our highlight is the proposal of a paradigm that draws on prior knowledge to instruct adaptive learning of vision and text representations.
Ranked #4 on Cross-Modal Retrieval on RSICD
no code implementations • 12 Oct 2023 • Qing Ma, Jiancheng Pan, Cong Bai
Our highlight is to conduct visual and textual representations in latent space, directing them as close as possible to a redundancy-free regional visual representation.
Ranked #5 on Cross-Modal Retrieval on RSITMD
1 code implementation • 10 Aug 2023 • Pan Mu, Hanning Xu, Zheyuan Liu, Zheng Wang, Sixian Chan, Cong Bai
To tackle these challenges, we design a Generalized Underwater image enhancement method via a Physical-knowledge-guided Dynamic Model (short for GUPDM), consisting of three parts: Atmosphere-based Dynamic Structure (ADS), Transmission-guided Dynamic Structure (TDS), and Prior-based Multi-scale Structure (PMS).
no code implementations • 10 Aug 2023 • Defang Cai, Pan Mu, Sixian Chan, Zhanpeng Shao, Cong Bai
As a common natural weather condition, rain can obscure video frames and thus affect the performance of the visual system, so video derain receives a lot of attention.
no code implementations • 9 Aug 2023 • Zheyuan Liu, Pan Mu, Hanning Xu, Cong Bai
Video colorization, aiming at obtaining colorful and plausible results from grayish frames, has aroused a lot of interest recently.
no code implementations • 9 Aug 2023 • Pan Mu, Jing Fang, Haotian Qian, Cong Bai
To deal with the color deviation problem, we design a Dynamic Color-guided Module (DCM) to post-process the enhanced image color.
2 code implementations • ICMR 2023 • Jiancheng Pan, Qing Ma, Cong Bai
Furthermore, as the diversity and differentiation of remote sensing scenes weaken the understanding of scenes, a new metric, namely, scene recall is proposed to measure the perception of scenes by evaluating scene-level retrieval performance, which can also verify the effectiveness of our approach in reducing semantic confusion.
Ranked #6 on Cross-Modal Retrieval on RSICD
1 code implementation • 11 Jul 2022 • Jianan Chen, Lu Zhang, Qiong Wang, Cong Bai, Kidiyo Kpalma
Cross-modal retrieval has drawn much attention in both computer vision and natural language processing domains.
no code implementations • 5 May 2022 • Feng Sun, Cong Bai
To address this problem, we propose a novel Multi-frame-to-Multi-frame Inference (MMI) model with Noise Resistance (NR) named MMINR.
no code implementations • IEEE Geoscience and Remote Sensing Letters 2022 • Cong Bai, Feng Sun, Jinglin Zhang, Yi Song, ShengYong Chen
The experimental results show that Rainformer outperforms seven state of the arts methods on the benchmark database and provides more insights into the high-intensity rainfall prediction task.
Ranked #5 on Weather Forecasting on SEVIR
1 code implementation • 23 Feb 2022 • Kaining Ying, Zhenhua Wang, Cong Bai, Pengfei Zhou
Most instance segmentation models are not end-to-end trainable due to either the incorporation of proposal estimation (RPN) as a pre-processing or non-maximum suppression (NMS) as a post-processing.
Ranked #17 on Instance Segmentation on COCO test-dev (APL metric)