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- StackGAN: Text to Photo-Realistic Image Synthesis with Stacked Generative Adversarial Networks2,975
This paper proposes Stacked Generative Adversarial Networks (StackGAN) to generate 256 photo-realistic images conditioned on text descriptions and introduces a novel Conditioning Augmentation technique that encourages smoothness in the latent conditioning manifold.
- StackGAN++: Realistic Image Synthesis with Stacked Generative Adversarial Networks1,198
Extensive experiments demonstrate that the proposed stacked generative adversarial networks significantly outperform other state-of-the-art methods in generating photo-realistic images.
- Engineering and Algorithm Design for an Image Processing API: A Technical Report on ITK - the Insight Toolkit745
The detailed planning and execution of the Insight Toolkit (ITK), an application programmers interface (API) for the segmentation and registration of medical image data, is presented.
- Learning with structured sparsity571
This paper investigates a new learning formulation called structured sparsity, which is a natural extension of the standard sparsity concept in statistical learning and compressive sensing by allowing arbitrary structures on the feature set, which generalizes the group sparsity idea.
- SVDiff: Compact Parameter Space for Diffusion Fine-Tuning429
The proposed SVDiff method involves fine-tuning the singular values of the weight matrices, leading to a compact and efficient parameter space that reduces the risk of overfitting and language-drifting, making it more practical for real-world applications.
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- An anthropometric face model using variational techniques377
A system that automatically generates varied geometric models of human faces according to anthropometric statistics for likely face measurements in a population using Variational modeling to find a smooth surface that satisfies constraints while using a prototype shape as a reference.
- A Framework for Recognizing the Simultaneous Aspects of American Sign Language364
This paper presents a novel framework to ASL recognition that aspires to being a solution to the scalability problems, based on breaking down the signs into their phonemes and modeling them with parallel hidden Markov models.
- Optical Flow Constraints on Deformable Models with Applications to Face Tracking360
A dynamic system incorporating flow as a hard constraint is derived and solved, producing a model-based least-squares optical flow solution that ensures the constraint remains satisfied when combined with edge information, which helps combat tracking error accumulation.
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- Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectors329
This work extends the horizontal keypoint-based object detector to the oriented object detection task, and shows that learning the box boundary-aware vectors is superior to directly predicting the width, height, and angle of an oriented bounding box, as adopted in the baseline method.
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- Autism: the micro-movement perspective257
The methods address the heterogeneity of ASD with a personalized approach grounded in the inherent sensory-motor abilities that the individual has already developed, based on the non-stationary stochastic patterns of minute fluctuations inherent to the authors' natural actions.
- Automatic Liver Segmentation Using an Adversarial Image-to-Image Network249
This paper proposes an automatic and efficient algorithm to segment liver from 3D CT volumes using a deep image-to-image network employing a convolutional encoder-decoder architecture combined with multi-level feature concatenation and deep supervision.
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- Novel method for high-throughput phenotyping of sleep in mice245
The method gives excellent agreement in C57BL/6J male mice with simultaneous assessment of sleep by EEG/EMG recording and has applications in chemical mutagenesis and for studies of molecular changes in brain with sleep/wakefulness.
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- Semantic Amodal Segmentation228
A detailed image annotation that captures information beyond the visible pixels and requires complex reasoning about full scene structure is proposed, and it is shown that the proposed full scene annotation is surprisingly consistent between annotators, including for regions and edges.
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- Jointly Optimize Data Augmentation and Network Training: Adversarial Data Augmentation in Human Pose Estimation226
The key idea is to design a generator that competes against a discriminator that explores weaknesses of the discriminators, while the discriminator learns from hard augmentations to achieve better performance.
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- SINE: SINgle Image Editing with Text-to-Image Diffusion Models220
A novel model-based guidance built upon the classifier-free guidance is proposed so that the knowledge from the model trained on a single image can be distilled into the pre-trained diffusion model, enabling content creation even with one given image.
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Publication data from OpenAlex, with missing venues and authors filled in from Crossref; citation counts are the higher of OpenAlex and Semantic Scholar, last synced 2026-10-15. One-sentence summaries under some papers are written by Semantic Scholar’s model. Citation counts may be lower than on Google Scholar, which indexes more sources.
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