CoSTA: Cost-Sensitive Toolpath Agent for Multi-turn Image Editing
Introduces CoSTA*, a novel cost-sensitive toolpath agent for multi-turn image editing, combining large language models (LLMs) and A* search to optimiz...
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Introduces CoSTA*, a novel cost-sensitive toolpath agent for multi-turn image editing, combining large language models (LLMs) and A* search to optimiz...
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Presents a novel approach to face age progression using a Generative Adversarial Network (GAN) that specifically addresses the challenges of aging acc...
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Presents LiftedGAN, a framework that facilitates self-supervised, 3D-aware face generation using a distillation approach from a pre-trained StyleGAN2 ...
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Presents WarpGAN, an automated neural network designed for generating caricatures from face photographs. It focuses on maintaining identity while tran...
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With recent advances in image and video diffusion models for content creation, a plethora of techniques have been proposed for customizing their gener...
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Canonical emotions, such as happy, sad, and fearful, are easy to understand and annotate. However, emotions are often compound, e.g. happily surprised...
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The increased importance of mobile photography created a need for fast and performant RAW image processing pipelines capable of producing good visual ...
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Introduces Pix2NeRF, a groundbreaking unsupervised framework that translates a single input image into Neural Radiance Fields (NeRF) for novel view sy...
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Aims to conduct a comprehensive study on facial-sketch synthesis (FSS). However, due to the high costs of obtaining hand-drawn sketch datasets, there ...
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Addresses the challenges of logo design by employing Clustered Generative Adversarial Networks (GANs) to automate the synthesis and manipulation of lo...
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We propose a trainable Image Signal Processing (ISP) framework that produces DSLR quality images given RAW images captured by a smartphone. To address...
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Video super-resolution (VSR) has many applications that pose strict causal, real-time, and latency constraints, including video streaming and TV. We a...
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