1.4k citations · 4.9k across the 44 of their papers we have counts for
5 papers · 1 filter
Image-based localization using LSTMs for structured feature correlation
Florian Walch, Caner Hazirbas, Laura Leal-Taixé +3
In this work we propose a new CNN+LSTM architecture for camera pose regression for indoor and outdoor scenes. CNNs allow us to learn suitable feature representations for localizati…
One-Shot Video Object Segmentation
Sergi Caelles, Kevis-Kokitsi Maninis, Jordi Pont-Tuset +3
This paper tackles the task of semi-supervised video object segmentation, i.e., the separation of an object from the background in a video, given the mask of the first frame. We pr…
Tracking with multi-level features
Roberto Henschel, Laura Leal-Taixé, Bodo Rosenhahn +1
We present a novel formulation of the multiple object tracking problem which integrates low and mid-level features. In particular, we formulate the tracking problem as a quadratic…
Learning by tracking: Siamese CNN for robust target association
Laura Leal-Taixé, Cristian Canton Ferrer, Konrad Schindler
This paper introduces a novel approach to the task of data association within the context of pedestrian tracking, by introducing a two-stage learning scheme to match pairs of detec…
MOT16: A Benchmark for Multi-Object Tracking
Anton Milan, Laura Leal-Taixe, Ian Reid +2
Standardized benchmarks are crucial for the majority of computer vision applications. Although leaderboards and ranking tables should not be over-claimed, benchmarks often provide…