7 accepted papers
Multi-view diabetic retinopathy (DR) grading has achieved remarkable performance by capturing more comprehensive pathological features than single-view methods. However, complete multi-view fundus images are often difficult to obtain in clinical practice, and the performance degrades significantly w
The advancement in multimodal research has increased focus on Emotion Recognition in Conversations (ERC), targeting accurately identifying emotional changes. Methods based on graph convolution can better capture the dynamic changes of emotions and improve the accuracy and robustness of emotion recog…
We propose a semantic priori-guided scalable image coding method for simultaneously supporting fast machine vision analysis and high quality human visual experience. To obtain high-performance machine vision analysis results with a more compact base layer bitrate, our base layer directly encodes int…
Facial expression recognition (FER) methods are fundamental in various human-computer interaction scenarios. Although deep learning-based models have made substantial progress in the FER field, they primarily focus on capturing facial appearance features while neglecting the importance of structure…
Existing emotion recognition methods in conversations (ERC) focus on using different utterances information between speakers to improve emotion recognition performance, but they ignore the differential contributions of different utterances to emotion recognition. In this paper, we propose a speaker-…
Recent image inpainting methods based on end-to-end models have achieved great success with the help of generative adversarial training and structure generation. However, the generated conditional structure priors cannot support the model to reconstruct finer texture. This is mainly because these mo…
Recently, deep learning based image Compressed Sensing (CS) methods have been proposed and demonstrated superior reconstruction quality with low computational complexity. However, the existing deep learning based image CS methods need to train different models for different sampling ratios, which in…