Search Results for author:
Found 10 papers, 2 papers with code
Motion Classification Based on Harmonic Micro-Doppler Signatures Using a Convolutional Neural Network
We demonstrate the classification of common motions of held objects using the harmonic micro-Doppler signatures scattered from harmonic radio-frequency tags.
A linearized framework and a new benchmark for model selection for fine-tuning
Since all model selection algorithms in the literature have been tested on different use-cases and never compared directly, we introduce a new comprehensive benchmark for model selection comprising of: i) A model zoo of single and multi-domain models, and ii) Many target tasks.
Fast, Diverse and Accurate Image Captioning Guided By Part-of-Speech
We achieve the trifecta: (1) High accuracy for the diverse captions as evaluated by standard captioning metrics and user studies; (2) Faster computation of diverse captions compared to beam search and diverse beam search; and (3) High diversity as evaluated by counting novel sentences, distinct n-grams and mutual overlap (i. e., mBleu-4) scores.
Convolutional Image Captioning
In recent years significant progress has been made in image captioning, using Recurrent Neural Networks powered by long-short-term-memory (LSTM) units.
Learning Diverse Image Colorization
Finally, we build a conditional model for the multi-modal distribution between grey-level image and the color field embeddings.
Authoring image decompositions with generative models
Instead, we can learn to decompose an image into layers that are "like this" by authoring generative models for each layer using proxy examples that capture the Platonic ideal (Mondrian images for albedo; rendered 3D primitives for shading; material swatches for shading detail).
CDVAE: Co-embedding Deep Variational Auto Encoder for Conditional Variational Generation
Such a model is difficult to train, because we do not usually have training data containing many different shadings for the same image.
Multistage SFM: A Coarse-to-Fine Approach for 3D Reconstruction
We present a multistage approach for SFM reconstruction of a single component that breaks the sequential nature of the incremental SFM methods.
Learning Large-Scale Automatic Image Colorization
The coefficients of the objective function are conditioned on image features, using a random forest.
