Text-guided image generation has advanced rapidly with large-scale diffusion models, yet achieving precise stylization with visual exemplars remains difficult. Existing approaches often depend on task-specific retraining or expensive inversion proced...
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In this work, we aim at automatically labeling actors in a TV series. Rather than relying on transcripts and subtitles, as has been demonstrated in the past, we show how to achieve this goal starting from a set of example images of each of the main a...
Mar 15, 2025 · This second-century graffito of a Roman crucifixion from Puteoli, Italy, is one of a few ancient crucifixion images that offer a first-hand glimpse of Roman crucifixion methods and what …
Contained within this volume are the scholarly contributions presented in both oral and poster formats at Fully3D 2023: The 17th International Meeting on Fully Three-Dimensional Image Reconstruction in Radiology and Nuclear Medicine. This conference...
We introduce Hair-GANs, an architecture of generative adversarial networks, to recover the 3D hair structure from a single image. The goal of our networks is to build a parametric transformation from 2D hair maps to 3D hair structure. The 3D hair str...
2 days ago · Iranian missiles and drones have hit the United Arab Emirates, shaking Dubai’s image as a safe, tax-free haven for foreigners.
Low-light image enhancement (LLIE) is essential for numerous computer vision tasks, including object detection, tracking, segmentation, and scene understanding. Despite substantial research on improving low-quality images captured in underexposed con...
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Natural language and images are commonly used as goal representations in goal-conditioned imitation learning (IL). However, natural language can be ambiguous and images can be over-specified. In this work, we propose hand-drawn sketches as a modality...
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Contrastive Language-Image Pretraining (CLIP) has shown impressive zero-shot performance on image classification. However, state-of-the-art methods often rely on fine-tuning techniques like prompt learning and adapter-based tuning to optimize CLIP's...
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