cara



My name is Joao Carreira. I am a postdoctoral scholar in Prof. Jitendra Malik's group at EECS, UC Berkeley.
My research targets the development of techniques that make it possible to robustly recover rich and accurate descriptions of objects from a single image, in particular of their shapes. My full cv is here.

I did my Ph.D. with Prof. Cristian Sminchisescu in the formidable group he had at the University of Bonn, working on segmentation and recognition techniques. We did a lot of noise on the Pascal VOC Challenges.
Afterwards I did postdoctoral work in Prof. Jorge Batista's awesome group in ISR-Coimbra, with which I am also affiliated. My full list of publications and corresponding bibtex files can be consulted on my google scholar account .

Email: carreira at eecs.berkeley.edu

News:

Recent publications

J. Carreira, R. Caseiro, J. Batista and C. Sminchisescu. Free-Form Region Description with Second-Order Pooling.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2014. pdf

C. Premebida, J. Carreira, J. Batista, U. Nunes. Pedestrian Detection Combining RGB and Dense Lidar Data.
In IROS 2014. pdf project/code

S. Vicente*, J. Carreira*, L. Agapito and J. Batista. Reconstructing PASCAL VOC. [Oral]
In CVPR 2014. (* first two authors contributed equally) pdf supp. material project/code slides talk

C. Ionescu, J. Carreira and C. Sminchisescu. Iterated Second-Order Label Sensitive Pooling for 3D Human Pose Estimation. [Oral]
In CVPR 2014. pdf project talk

A. Ion, J. Carreira, C. Sminchisescu. Probabilistic Joint Image Segmentation and Labeling by Figure-Ground Composition.
In International Journal of Computer Vision (IJCV), March 2014. pdf

J. F. Henriques, J. Carreira, R. Caseiro, J. Batista. Beyond Hard Negative Mining: Efficient Detector Learning via Block-Circulant Decomposition. [Oral]
In International Conference on Computer Vision (ICCV), December 2013. pdf supp. material project/code talk

F. Li, J. Carreira, G. Lebanon, C. Sminchisescu. Composite Statistical Inference for Semantic Segmentation.
In IEEE Conference on Computer Vision and Pattern Recognition (CVPR), June 2013. pdf

J. Carreira. Bottom-Up Object Segmentation for Visual Recognition.
Doctoral Thesis. University of Bonn, December 2012. pdf

J. Carreira, R. Caseiro, J. Batista and C. Sminchisescu. Semantic Segmentation with Second-Order Pooling. [Oral]
In European Conference on Computer Vision (ECCV), October 2012. pdf project/code slides talk

J. Carreira and C. Sminchisescu. CPMC: Automatic Object Segmentation Using Constrained Parametric Min-Cuts.
In IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), July 2012. pdf project/code

J. Carreira*, F. Li* and C. Sminchisescu. Object Recognition by Sequential Figure-Ground Ranking.
In International Journal of Computer Vision (IJCV), July 2012. (* first two authors contributed equally) pdf

A. Ion, J. Carreira and C. Sminchisescu. Probabilistic Joint Image Segmentation and Labeling. [Spotlight presentation]
In Advances in Neural Information Processing Systems (NIPS), December 2011. pdf

A. Ion, J. Carreira and C. Sminchisescu. Image Segmentation by Figure-Ground Composition into Maximal Cliques.
In IEEE International Conference on Computer Vision (ICCV), November 2011. pdf supp. material

J. Carreira, A. Ion and C. Sminchisescu. Image Segmentation by Discounted Cumulative Ranking on Maximal Cliques.
Technical Report 06-2010 (arXiv:1009.4823), Computer Vision and Machine Learning Group, Institute for Numerical Simulation, University of Bonn, June 2010. pdf

J. Carreira and C. Sminchisescu. Constrained Parametric Min-Cuts for Automatic Object Segmentation.
In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2010. pdf

F. Li*, J. Carreira* and C. Sminchisescu. Object Recognition as Ranking Holistic Figure-Ground Hypotheses.
In IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June 2010. (* first two authors contributed equally) pdf

J. Carreira, F. Li and C. Sminchisescu. Object Recognition by Ranking Figure-Ground Hypotheses.
Snowbird Learning, April 2010.pdf


Last actualization on 18-09-2014.