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Found 16 papers, 9 papers with code
AnaMoDiff: 2D Analogical Motion Diffusion via Disentangled Denoising
We present AnaMoDiff, a novel diffusion-based method for 2D motion analogies that is applied to raw, unannotated videos of articulated characters.
Slice3D: Multi-Slice, Occlusion-Revealing, Single View 3D Reconstruction
Our key observation is that object slicing is more advantageous than altering views to reveal occluded structures.
Experimental quantum natural gradient optimization in photonics
Our work opens up a vista of utilizing QNG in photonics to implement practical near-term quantum applications.
Quantum generative adversarial learning in photonics
Quantum Generative Adversarial Networks (QGANs), an intersection of quantum computing and machine learning, have attracted widespread attention due to their potential advantages over classical analogs.
BRICS: Bi-level feature Representation of Image CollectionS
Our key codes and feature grids are jointly trained continuously with well-defined gradient flows, leading to high usage rates of the feature grids and improved generative modeling compared to discrete Vector Quantization (VQ).
DeepVecFont-v2: Exploiting Transformers to Synthesize Vector Fonts with Higher Quality
First, we adopt Transformers instead of RNNs to process sequential data and design a relaxation representation for vector outlines, markedly improving the model's capability and stability of synthesizing long and complex outlines.
DS-Fusion: Artistic Typography via Discriminated and Stylized Diffusion
We introduce a novel method to automatically generate an artistic typography by stylizing one or more letter fonts to visually convey the semantics of an input word, while ensuring that the output remains readable.
ARO-Net: Learning Implicit Fields from Anchored Radial Observations
We introduce anchored radial observations (ARO), a novel shape encoding for learning implicit field representation of 3D shapes that is category-agnostic and generalizable amid significant shape variations.
Aesthetic Text Logo Synthesis via Content-aware Layout Inferring
To train and evaluate our approach, we construct a dataset named as TextLogo3K, consisting of about 3, 500 text logo images and their pixel-level annotations.
DeepVecFont: Synthesizing High-quality Vector Fonts via Dual-modality Learning
Automatic font generation based on deep learning has aroused a lot of interest in the last decade.
Exploring Font-independent Features for Scene Text Recognition
Scene text recognition (STR) has been extensively studied in last few years.
Attribute2Font: Creating Fonts You Want From Attributes
To the best of our knowledge, our model is the first one in the literature which is capable of generating glyph images in new font styles, instead of retrieving existing fonts, according to given values of specified font attributes.
muSSP: Efficient Min-cost Flow Algorithm for Multi-object Tracking
Min-cost flow has been a widely used paradigm for solving data association problems in multi-object tracking (MOT).
Efficient Global Multi-object Tracking Under Minimum-cost Circulation Framework
When our method served as a sub-module for global data association methods using higher-order constraints, similar efficiency improvement was attained.
Boosting Scene Character Recognition by Learning Canonical Forms of Glyphs
In this paper, we propose a novel methodology for boosting scene character recognition by learning canonical forms of glyphs, based on the fact that characters appearing in scene images are all derived from their corresponding canonical forms.
Graphical Time Warping for Joint Alignment of Multiple Curves
We name the proposed approach graphical time warping (GTW), emphasizing the graphical nature of the solution and that the dependency structure of the warping functions can be represented by a graph.
