Search Results for author:
Found 12 papers, 6 papers with code
Little Strokes Fell Great Oaks: Boosting the Hierarchical Features for Multi-exposure Image Fusion
In recent years, deep learning networks have made remarkable strides in the domain of multi-exposure image fusion.
A Prior Instruction Representation Framework for Remote Sensing Image-text Retrieval
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
Direction-Oriented Visual-semantic Embedding Model for Remote Sensing Image-text Retrieval
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
A Generalized Physical-knowledge-guided Dynamic Model for Underwater Image Enhancement
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).
Towards General and Fast Video Derain via Knowledge Distillation
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.
Histogram-guided Video Colorization Structure with Spatial-Temporal Connection
Video colorization, aiming at obtaining colorful and plausible results from grayish frames, has aroused a lot of interest recently.
Transmission and Color-guided Network for Underwater Image Enhancement
To deal with the color deviation problem, we design a Dynamic Color-guided Module (DCM) to post-process the enhanced image color.
Reducing Semantic Confusion: Scene-aware Aggregation Network for Remote Sensing Cross-modal Retrieval
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
Intra-Modal Constraint Loss For Image-Text Retrieval
Cross-modal retrieval has drawn much attention in both computer vision and natural language processing domains.
MMINR: Multi-frame-to-Multi-frame Inference with Noise Resistance for Precipitation Nowcasting with Radar
To address this problem, we propose a novel Multi-frame-to-Multi-frame Inference (MMI) model with Noise Resistance (NR) named MMINR.
Rainformer: Features Extraction Balanced Network for Radar-Based Precipitation Nowcasting
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
ISDA: Position-Aware Instance Segmentation with Deformable Attention
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)
