Extensive experimental results show that training on the automatically generated optical flow outperforms methods that are trained on rigid synthetic data using FlowNet-S, LiteFlowNet, PWC-Net, PWC-Net, and RAFT.
Visual perception in dynamic scenes is a crucial task in the fields of computer vision and autonomous driving. In this paper, we focus on monocular optical flow and expansion estimation. Optical flow describes the positional changes of pixels between two frames, while optical expansion describes local image-scale chang...
Chang-Lin Li, Ye-Qiang Qian, Chun-Xiang Wang et al.· IEEE Transactions on Pattern...· 0 citations
A method to train a 3D object detector from a single RGB camera without domain-specific human annotations, making orders of magnitude more data available for training and shows that combining pseudo-labels from multiple datasets can achieve comparable accuracy to using human labels from a single dataset.
Jan Skvrna, Lukás Neumann· International Journal of Com...· 0 citations
This work proposes albedo and shading gradient descriptors which are derived from physics-based models and is the first to directly address the texture and intensity ambiguity problems of the shading estimations.
A. S. Baslamisli, Yang Liu, Sezer Karaoglu et al.· 0 citations
Pixel-level annotation of fixed traffic-camera imagery is expensive, while crosswalk models trained from street-level imagery face a substantial viewpoint and appearance shift when applied to elevated CCTV. We investigate a data-efficient target-domain pipeline using 241 manually annotated CCTV images and 5,926 unlabel...
Precise control over camera and object motion is essential for professional video production. Existing methods control objects only coarsely, through image-plane cues that are ambiguous in depth and rotation or through 3D tracks and blobs that lack complete geometry and lose consistency across viewpoint changes. We int...
Wei Cao, Hao Zhang, Vikram Voleti et al.· 1 citation
A biologically inspired framework for learning object-centric visual representations in an unsupervised manner, suggesting that motion-induced object representations offer a compelling alternative to existing vision foundation models, capturing a crucial but overlooked level of abstraction: the visual instance.
Hao Liang, Xiao-Hui Wang, Zhi-Chao Li et al.· Neural Information Processin...· 0 citations
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