1 citations · 1 across the 2 of their papers we have counts for
7 papers
OS2D: One-Stage One-Shot Object Detection by Matching Anchor Features
Anton Osokin, Denis Sumin, Vasily Lomakin
In this paper, we consider the task of one-shot object detection, which consists in detecting objects defined by a single demonstration. Differently from the standard object detect…
Cost-Sensitive Training for Autoregressive Models
Irina Saparina, Anton Osokin
Training autoregressive models to better predict under the test metric, instead of maximizing the likelihood, has been reported to be beneficial in several use cases but brings add…
Scaling Matters in Deep Structured-Prediction Models
Aleksandr Shevchenko, Anton Osokin
Deep structured-prediction energy-based models combine the expressive power of learned representations and the ability of embedding knowledge about the task at hand into the system…
Tube-CNN: Modeling temporal evolution of appearance for object detection in video
Tuan-Hung Vu, Anton Osokin, Ivan Laptev
Object detection in video is crucial for many applications. Compared to images, video provides additional cues which can help to disambiguate the detection problem. Our goal in thi…
Marginal Weighted Maximum Log-likelihood for Efficient Learning of Perturb-and-Map models
Tatiana Shpakova, Francis Bach, Anton Osokin
We consider the structured-output prediction problem through probabilistic approaches and generalize the "perturb-and-MAP" framework to more challenging weighted Hamming losses, wh…
GANs for Biological Image Synthesis
Anton Osokin, Anatole Chessel, Rafael E. Carazo Salas +1
In this paper, we propose a novel application of Generative Adversarial Networks (GAN) to the synthesis of cells imaged by fluorescence microscopy. Compared to natural images, cell…