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20162022
most citedDomain Adaptation for Object Detection via Style Consistency

60 citations · 89 across the 12 of their papers we have counts for

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21 papers · 1 filter

cs.CV20221 cited

ObjCAViT: Improving Monocular Depth Estimation Using Natural Language Models And Image-Object Cross-Attention

Dylan Auty, Krystian Mikolajczyk

While monocular depth estimation (MDE) is an important problem in computer vision, it is difficult due to the ambiguity that results from the compression of a 3D scene into only 2…

cs.CV2022

Monocular Depth Estimation Using Cues Inspired by Biological Vision Systems

Dylan Auty, Krystian Mikolajczyk

Monocular depth estimation (MDE) aims to transform an RGB image of a scene into a pixelwise depth map from the same camera view. It is fundamentally ill-posed due to missing inform…

cs.CV20211 cited

Grasp-Oriented Fine-grained Cloth Segmentation without Real Supervision

Ruijie Ren, Mohit Gurnani Rajesh, Jordi Sanchez-Riera +6

Automatically detecting graspable regions from a single depth image is a key ingredient in cloth manipulation. The large variability of cloth deformations has motivated most of the…

cs.CV202111 cited

Reassessing the Limitations of CNN Methods for Camera Pose Regression

Tony Ng, Adrian Lopez-Rodriguez, Vassileios Balntas +1

In this paper, we address the problem of camera pose estimation in outdoor and indoor scenarios. In comparison to the currently top-performing methods that rely on 2D to 3D matchin…

cs.CV20204 cited

DESC: Domain Adaptation for Depth Estimation via Semantic Consistency

Adrian Lopez-Rodriguez, Krystian Mikolajczyk

Accurate real depth annotations are difficult to acquire, needing the use of special devices such as a LiDAR sensor. Self-supervised methods try to overcome this problem by process…

cs.CV20207 cited

Cascaded channel pruning using hierarchical self-distillation

Roy Miles, Krystian Mikolajczyk

In this paper, we propose an approach for filter-level pruning with hierarchical knowledge distillation based on the teacher, teaching-assistant, and student framework. Our method…