2.2k citations · 7.1k across the 72 of their papers we have counts for
10 papers · 1 filter
Practical Text Classification With Large Pre-Trained Language Models
Neel Kant, Raul Puri, Nikolai Yakovenko +1
Multi-emotion sentiment classification is a natural language processing (NLP) problem with valuable use cases on real-world data. We demonstrate that large-scale unsupervised langu…
Improving Semantic Segmentation via Video Propagation and Label Relaxation
Yi Zhu, Karan Sapra, Fitsum A. Reda +4
Semantic segmentation requires large amounts of pixel-wise annotations to learn accurate models. In this paper, we present a video prediction-based methodology to scale up training…
Partial Convolution based Padding
Guilin Liu, Kevin J. Shih, Ting-Chun Wang +5
In this paper, we present a simple yet effective padding scheme that can be used as a drop-in module for existing convolutional neural networks. We call it partial convolution base…
An Interpretable Model for Scene Graph Generation
Ji Zhang, Kevin Shih, Andrew Tao +2
We propose an efficient and interpretable scene graph generator. We consider three types of features: visual, spatial and semantic, and we use a late fusion strategy such that each…
Introduction to the 1st Place Winning Model of OpenImages Relationship Detection Challenge
Ji Zhang, Kevin Shih, Andrew Tao +2
This article describes the model we built that achieved 1st place in the OpenImage Visual Relationship Detection Challenge on Kaggle. Three key factors contribute the most to our s…
SDCNet: Video Prediction Using Spatially-Displaced Convolution
Fitsum A. Reda, Guilin Liu, Kevin J. Shih +5
We present an approach for high-resolution video frame prediction by conditioning on both past frames and past optical flows. Previous approaches rely on resampling past frames, gu…