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Towards Generic and Controllable Attacks Against Object Detection
Guopeng Li, Yue Xu, Jian Ding +1
Existing adversarial attacks against Object Detectors (ODs) suffer from two inherent limitations. Firstly, ODs have complicated meta-structure designs, hence most advanced attacks…
NEAT: Distilling 3D Wireframes from Neural Attraction Fields
Nan Xue, Bin Tan, Yuxi Xiao +4
This paper studies the problem of structured 3D reconstruction using wireframes that consist of line segments and junctions, focusing on the computation of structured boundary geom…
Depth and DOF Cues Make A Better Defocus Blur Detector
Yuxin Jin, Ming Qian, Jincheng Xiong +2
Defocus blur detection (DBD) separates in-focus and out-of-focus regions in an image. Previous approaches mistakenly mistook homogeneous areas in focus for defocus blur regions, li…
HGFormer: Hierarchical Grouping Transformer for Domain Generalized Semantic Segmentation
Jian Ding, Nan Xue, Gui-Song Xia +2
Current semantic segmentation models have achieved great success under the independent and identically distributed (i.i.d.) condition. However, in real-world applications, test dat…
FreePoint: Unsupervised Point Cloud Instance Segmentation
Zhikai Zhang, Jian Ding, Li Jiang +2
Instance segmentation of point clouds is a crucial task in 3D field with numerous applications that involve localizing and segmenting objects in a scene. However, achieving satisfa…
Sat2Density: Faithful Density Learning from Satellite-Ground Image Pairs
Ming Qian, Jincheng Xiong, Gui-Song Xia +1
This paper aims to develop an accurate 3D geometry representation of satellite images using satellite-ground image pairs. Our focus is on the challenging problem of 3D-aware ground…
Learning to Super-Resolve Blurry Images with Events
Lei Yu, Bishan Wang, Xiang Zhang +4
Super-Resolution from a single motion Blurred image (SRB) is a severely ill-posed problem due to the joint degradation of motion blurs and low spatial resolution. In this paper, we…
Few-Shot Object Detection via Variational Feature Aggregation
Jiaming Han, Yuqiang Ren, Jian Ding +2
As few-shot object detectors are often trained with abundant base samples and fine-tuned on few-shot novel examples,the learned models are usually biased to base classes and sensit…
Detecting Building Changes with Off-Nadir Aerial Images
Chao Pang, Jiang Wu, Jian Ding +2
The tilted viewing nature of the off-nadir aerial images brings severe challenges to the building change detection (BCD) problem: the mismatch of the nearby buildings and the seman…