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Found 14 papers, 3 papers with code
ACDG-VTON: Accurate and Contained Diffusion Generation for Virtual Try-On
Virtual Try-on (VTON) involves generating images of a person wearing selected garments.
Me LLaMA: Foundation Large Language Models for Medical Applications
In response to this challenge, this study introduces Me-LLaMA, a novel medical LLM family that includes foundation models - Me-LLaMA 13/70B, along with their chat-enhanced versions - Me-LLaMA 13/70B-chat, developed through continual pre-training and instruction tuning of LLaMA2 using large medical datasets.
Preserving Image Properties Through Initializations in Diffusion Models
The usual practice of training the denoiser with a very noisy image and starting inference with a sample of pure noise leads to inconsistent generated images during inference.
Higher-Order Newton Methods with Polynomial Work per Iteration
At each step, our $d^{\text{th}}$-order method uses semidefinite programming to construct and minimize a sum of squares-convex approximation to the $d^{\text{th}}$-order Taylor expansion of the function we wish to minimize.
Wearing the Same Outfit in Different Ways -- A Controllable Virtual Try-on Method
However, no current method can both control how the garment is worn -- including tuck or untuck, opened or closed, high or low on the waist, etc.. -- and generate realistic images that accurately preserve the properties of the original garment.
Toward Accurate and Realistic Outfits Visualization with Attention to Details
Prior works produce images that are filled with artifacts and fail to capture important visual details necessary for commercial applications.
Dexterous Manipulation Primitives for the Real Robot Challenge
We use model-based trajectory optimization and control to plan and execute these primitives.
Robotics
Complexity Aspects of Fundamental Questions in Polynomial Optimization
These include the questions of (i) finding a local minimum, (ii) testing local minimality of a point, and (iii) deciding attainment of the optimal value.
Complexity aspects of local minima and related notions
We consider the notions of (i) critical points, (ii) second-order points, (iii) local minima, and (iv) strict local minima for multivariate polynomials.
On the complexity of finding a local minimizer of a quadratic function over a polytope
We show that unless P=NP, there cannot be a polynomial-time algorithm that finds a point within Euclidean distance $c^n$ (for any constant $c \ge 0$) of a local minimizer of an $n$-variate quadratic function over a polytope.
Memory-Efficient Incremental Learning Through Feature Adaptation
We assume that the model is updated incrementally for new classes as new data becomes available sequentially. This requires adapting the previously stored feature vectors to the updated feature space without having access to the corresponding original training images.
Generalized Latent Variable Recovery for Generative Adversarial Networks
The Generator of a Generative Adversarial Network (GAN) is trained to transform latent vectors drawn from a prior distribution into realistic looking photos.
Automated and Interpretable Patient ECG Profiles for Disease Detection, Tracking, and Discovery
We identified 36, 186 ECGs from the UCSF database that were 1) in normal sinus rhythm and 2) would enable training of specific models for estimation of cardiac structure or function or detection of disease.
A Computer Vision Pipeline for Automated Determination of Cardiac Structure and Function and Detection of Disease by Two-Dimensional Echocardiography
Automated cardiac image interpretation has the potential to transform clinical practice in multiple ways including enabling low-cost serial assessment of cardiac function in the primary care and rural setting.
