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Fast optical flow using dense inverse search
(2016)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2016Conference Paper -
Metric imitation by manifold transfer for efficient vision applications
(2015)2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Conference Paper -
Joint vanishing point extraction and tracking
(2015)2015 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)Conference Paper -
Semantic Object Prediction and Spatial Sound Super-Resolution with Binaural Sounds
(2020)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2020Humans can robustly recognize and localize objects by integrating visual and auditory cues. While machines are able to do the same now with images, less work has been done with sounds. This work develops an approach for dense semantic labelling of sound-making objects, purely based on binaural sounds. We propose a novel sensor setup and record a new audio-visual dataset of street scenes with eight professional binaural microphones and a ...Conference Paper -
Domain Adaptive Faster R-CNN for Object Detection in the Wild
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionConference Paper -
Object Referring in Videos with Language and Human Gaze
(2018)2018 IEEE/CVF Conference on Computer Vision and Pattern RecognitionConference Paper -
TACS: Taxonomy Adaptive Cross-Domain Semantic Segmentation
(2022)Lecture Notes in Computer Science ~ Computer Vision – ECCV 2022Traditional domain adaptive semantic segmentation addresses the task of adapting a model to a novel target domain under limited or no additional supervision. While tackling the input domain gap, the standard domain adaptation settings assume no domain change in the output space. In semantic prediction tasks, different datasets are often labeled according to different semantic taxonomies. In many real-world settings, the target domain task ...Conference Paper -
Task Switching Network for Multi-task Learning
(2021)2021 IEEE/CVF International Conference on Computer Vision (ICCV)We introduce Task Switching Networks (TSNs), a task-conditioned architecture with a single unified encoder/decoder for efficient multi-task learning. Multiple tasks are performed by switching between them, performing one task at a time. TSNs have a constant number of parameters irrespective of the number of tasks. This scalable yet conceptually simple approach circumvents the overhead and intricacy of task-specific network components in ...Conference Paper -
Analogical Image Translation for Fog Generation
(2021)Proceedings of the AAAI Conference on Artificial IntelligenceImage-to-image translation is to map images from a given style to another given style. While exceptionally successful, current methods assume the availability of training images in both source and target domains, which does not always hold in practice. Inspired by humans' reasoning capability of analogy, we propose analogical image translation (AIT) that exploit the concept of gist, for the first time. Given images of two styles in the ...Conference Paper -
Jointly Learning Band Selection and Filter Array Design for Hyperspectral Imaging
(2023)2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)A single-shot multispectral camera equipped with an optimized color filter array (CFA) has the potential to deliver a fast and low-cost hyperspectral (HS) imaging system. Previous solutions are largely restricted to designing demosaicing algorithms for fixed CFAs – be it the Bayer color pattern or evenly-spaced spectral multiplexing patterns. Since sampling and reconstruction are tightly-coupled, the ability to search for an optimal ...Conference Paper