Papers Re-Ranking

The Best of Both Worlds: Combining Data-independent and Data-driven Approaches for Action Recognition

Motivated by the success of data-driven convolutional neural networks (CNNs) in object recognition on static images, researchers are working hard towards developing CNN equivalents for learning video features. However, l…

Bag-of-Words Forced Decoding for Cross-Lingual Information Retrieval

Recursive Partitioning for Heterogeneous Causal Effects

In this paper we study the problems of estimating heterogeneity in causal effects in experimental or observational studies and conducting inference about the magnitude of the differences in treatment effects across subse…

$gen$CNN: A Convolutional Architecture for Word Sequence Prediction

We propose a novel convolutional architecture, named $gen$CNN, for word sequence prediction. Different from previous work on neural network-based language modeling and generation (e.g., RNN or LSTM), we choose not to gre…

Phrase Based Language Model for Statistical Machine Translation: Empirical Study

Reordering is a challenge to machine translation (MT) systems. In MT, the widely used approach is to apply word based language model (LM) which considers the constituent units of a sentence as words. In speech recognitio…

From Captions to Visual Concepts and Back

This paper presents a novel approach for automatically generating image descriptions: visual detectors, language models, and multimodal similarity models learnt directly from a dataset of image captions. We use multiple …

Coarse-grained Candidate Generation and Fine-grained Re-ranking for Chinese Abbreviation Prediction

Aggregate channel features for multi-view face detection

Face detection has drawn much attention in recent decades since the seminal work by Viola and Jones. While many subsequences have improved the work with more powerful learning algorithms, the feature representation used …

Congruency-Based Reranking

We present a tool for re-ranking the results of a specific query by considering the (n+1) × (n+1) matrix of pairwise similarities among the elements of the set of n retrieved results and the query itself. The re-ranking …

Automatic Annotation of Machine Translation Datasets with Binary Quality Judgements

The automatic estimation of machine translation (MT) output quality is an active research area due to its many potential applications (e.g. aiding human translation and post-editing, re-ranking MT hypotheses, MT system c…

Automatic Extraction of Synonyms for German Particle Verbs from Parallel Data with Distributional Similarity as a Re-Ranking Feature

We present a method for the extraction of synonyms for German particle verbs based on a word-aligned German-English parallel corpus: by translating the particle verb to a pivot, which is then translated back, a set of sy…

Applying the semantics of negation to SMT through n-best list re-ranking

Word Confidence Estimation for SMT N-best List Re-ranking

Image Search Reranking

The existing methods for image search reranking suffer from the unfaithfulness of the assumptions under which the text-based images search result. The resulting images contain more irrelevant images. Hence the re ranking…

Response Generation Based on Hierarchical Semantic Structure with POMDP Re-ranking for Conversational Dialogue Systems

(Re)ranking Meets Morphosyntax: State-of-the-art Results from the SPMRL 2013 Shared Task

Minimum Bayes Risk based Answer Re-ranking for Question Answering

Joint multi-person detection and tracking from overlapping cameras

We present a system to track the positions of multiple persons in a scene from overlapping cameras. The distinguishing aspect of our method is a novel, two-step approach that jointly estimates person position and track…

SCALPEL: Segmentation Cascades with Localized Priors and Efficient Learning

We propose SCALPEL, a flexible method for object segmentation that integrates rich region-merging cues with midand high-level information about object layout, class, and scale into the segmentation process. Unlike compet…

Discriminative Re-ranking of Diverse Segmentations

This paper introduces a two-stage approach to semantic image segmentation. In the first stage a probabilistic model generates a set of diverse plausible segmentations. In the second stage, a discriminatively trained re-r…