Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Shaban, Amirreza"'
This work tackles the challenge of efficiently selecting high-performance pre-trained vision backbones for specific target tasks. Although exhaustive search within a finite set of backbones can solve this problem, it becomes impractical for large dat
Externí odkaz:
http://arxiv.org/abs/2410.08592
We introduce LiDAR-UDA, a novel two-stage self-training-based Unsupervised Domain Adaptation (UDA) method for LiDAR segmentation. Existing self-training methods use a model trained on labeled source data to generate pseudo labels for target data and
Externí odkaz:
http://arxiv.org/abs/2309.13523
Autor:
Meng, Xiangyun, Hatch, Nathan, Lambert, Alexander, Li, Anqi, Wagener, Nolan, Schmittle, Matthew, Lee, JoonHo, Yuan, Wentao, Chen, Zoey, Deng, Samuel, Okopal, Greg, Fox, Dieter, Boots, Byron, Shaban, Amirreza
Effective use of camera-based vision systems is essential for robust performance in autonomous off-road driving, particularly in the high-speed regime. Despite success in structured, on-road settings, current end-to-end approaches for scene predictio
Externí odkaz:
http://arxiv.org/abs/2303.15771
Despite recent advancements in deep learning, deep neural networks continue to suffer from performance degradation when applied to new data that differs from training data. Test-time adaptation (TTA) aims to address this challenge by adapting a model
Externí odkaz:
http://arxiv.org/abs/2206.00205
Detecting novel objects from few examples has become an emerging topic in computer vision recently. However, these methods need fully annotated training images to learn new object categories which limits their applicability in real world scenarios su
Externí odkaz:
http://arxiv.org/abs/2103.14162
Autor:
Li, Zhaoshuo, Shaban, Amirreza, Simard, Jean-Gabriel, Rabindran, Dinesh, DiMaio, Simon, Mohareri, Omid
Purpose: We describe a 3D multi-view perception system for the da Vinci surgical system to enable Operating room (OR) scene understanding and context awareness. Methods: Our proposed system is comprised of four Time-of-Flight (ToF) cameras rigidly at
Externí odkaz:
http://arxiv.org/abs/2003.09487
Weakly Supervised Object Localization (WSOL) methods only require image level labels as opposed to expensive bounding box annotations required by fully supervised algorithms. We study the problem of learning localization model on target classes with
Externí odkaz:
http://arxiv.org/abs/2003.08375
Predicting calibrated confidence scores for multi-class deep networks is important for avoiding rare but costly mistakes. A common approach is to learn a post-hoc calibration function that transforms the output of the original network into calibrated
Externí odkaz:
http://arxiv.org/abs/2003.06820
Publikováno v:
The IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2020
In late fusion, each modality is processed in a separate unimodal Convolutional Neural Network (CNN) stream and the scores of each modality are fused at the end. Due to its simplicity late fusion is still the predominant approach in many state-of-the
Externí odkaz:
http://arxiv.org/abs/1911.08670
Autor:
Shaban, Amirreza, Rahimi, Amir, Bansal, Shray, Gould, Stephen, Boots, Byron, Hartley, Richard
Given a collection of bags where each bag is a set of images, our goal is to select one image from each bag such that the selected images are from the same object class. We model the selection as an energy minimization problem with unary and pairwise
Externí odkaz:
http://arxiv.org/abs/1904.12936