- Image/Video Storage, Retrieval
- Image/Video Processing
- Image/Video Coding
- Image Scanning, Display, and Printing
- Image Formation

- Read more about Immersive Optical-See-Through Augmented Reality (Keynote Talk)
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Immersive Optical-See-Through Augmented Reality. Augmented Reality has been getting ready for the last 20 years, and is finally becoming real, powered by progress in enabling technologies such as graphics, vision, sensors, and displays. In this talk I’ll provide a personal retrospective on my journey, working on all those enablers, getting ready for the coming AR revolution. At Meta, we are working on immersive optical-see-through AR headset, as well as the full software stack. We’ll discuss the differences of optical vs.
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- Read more about SEMANTIC-EMBEDDED KNOWLEDGE ACQUISITION AND REASONING FOR IMAGE SEGMENTATION
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Image segmentation is a difficult and challenging task because of the complex object appearance and diverse object categories. Traditional methods directly use visual features for segmentation but ignore the correlation between objects. We introduce a knowledge reasoning module (KRM) for external knowledge aggregation and leverage a graphic neural network to aggregate the knowledge feature, which is concatenated with a visual feature for semantic segmentation. To this end, we use word embedding of category names as semantic feature and establish the relationship between categories.
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- Read more about IMAGE SEGMENTATION FOR IMPROVED LOSSLESS SCREEN CONTENT COMPRESSION
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In recent years, it has been found that screen content images (SCI) can be effectively compressed based on appropriate probability modelling and suitable entropy coding methods such as arithmetic coding. The key objective is determining the best probability distribution for each pixel position. This strategy works particularly well for images with synthetic (textual) content. However, usually screen content images not only consist of synthetic but also pictorial (natural) regions. These images require diverse models of probability distributions to be optimally compressed.
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- Read more about Image Generation is MAY All You Need for VQA
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Visual Question Answering (VQA) stands to benefit from the boost of increasingly sophisticated Pretrained Language Model (PLM) and Computer Vision-based models. In particular, many language modality studies have been conducted using image captioning or question generation with the knowledge ground of PLM in terms of data augmentation. However, image generation of VQA has been implemented in a limited way to modify only certain parts of the original image in order to control the quality and uncertainty.
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- Read more about GROUP-WISE CO-SALIENT OBJECT DETECTION WITH SIAMESE TRANSFORMERS VIA BROWNIAN DISTANCE COVARIANCE MATCHING
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- Read more about Compression Noise Reduction via Non-local Filtering with Rectified Regularity for Urban Building Scenes
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In this paper, we propose a novel low-rank based non-local image denoising method for HEVC video compression with the strategy of gathering non-local patches in the rectified domain. Owing to the irreversible quantization, image compression can be considered as adding noises into the original image, causing the distortion between the original image and the de-compressed image.
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- Read more about Image Compressed Sensing Using Auxiliary Information for Efficient Coding
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- Read more about SPECIALISED VIDEO QUALITY MODEL FOR ENHANCED USER GENERATED CONTENT (UGC) WITH SPECIAL EFFECTS
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- Read more about Meta Talk: Learning to Data-Efficiently Generate Audio-Driven Lip-Synchronized Talking Face with High Definition
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- Read more about SOLVING THE LONG-TAILED PROBLEM VIA INTRA- AND INTER-CATEGORY BALANCE
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poster.pdf

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