An encoder–decoder model which uses the image feature vectors as an input to the encoder is often marked as one of the appropriate models to accomplish the captioning process. In the proposed work, a dual-modal transformer has been used which captures the intra- and inter-model intera...
This paper proposes DualPromptIR, an advanced image restoration model designed to address the challenges of unpredictable and diverse degradation. While early methods relied on specialized encoders and decoders, there remains potential for performance enhancement. Recent research has explored learning ...
The coarse saliency maps are generated from an encoder-decoder framework which is trained with content loss and adversarial loss. The final results can be obtained via adaptive weighting of maps from each domain. Extensive experiments on two kinds of salient object detection benchmarks all obtained...
At the same time, semantic incompatibility exists because the feature maps of encoder and decoder are directly connected in the skip connection stage. In addition, in low light scenes such as at night, it is easy for false segmentation and segmentation accuracy to appear. To solve the above ...
At the same time, semantic incompatibility exists because the feature maps of encoder and decoder are directly connected in the skip connection stage. In addition, in low light scenes such as at night, it is easy for false segmentation and segmentation accuracy to appear. To solve t...
During the fusion process, both the encoder and decoder employ lightweight self-attention mechanisms. The encoder uses designed selection rules to precisely select salient features from the two branches, which are then fed into the decoder to achieve deep fusion. This decoder employs advanced image ...
Experimental results demonstrate that our efficient model using one common decoder block based on the DCMA to predict multiple events in the track-wise output format is effective for the SELD task with up to three overlapping events.Lee, Sang-Hoon...
We adopt an encoder–decoder framework to address the problem of visible–infrared dual-modal SOD. Figure 3 illustrates the overall architecture of the proposed DCFNet, which consists of a combined independent–shared encoder network and a multi-scale, multi-level decoder network. The encoder extract...
The decoder is used to reconstruct the dimension. At the same time, it ensures that important information about dimensionality reduction features is not lost. Figure 2. Overview of the proposed content common network. E denotes encoder structure, and D denotes decoder structure. The content common...
For different encoder feature maps, the self-attention module proposed in this paper performs adaptive feature fusion of the extracted long-wave and medium-wave infrared image features, which are then processed by the decoder for feature recovery and target prediction. Additionally, during model ...