Zobrazeno 1 - 10
of 51
pro vyhledávání: '"Chhatkuli, Ajad"'
Personalized 3D avatars require an animatable representation of digital humans. Doing so instantly from monocular videos offers scalability to broad class of users and wide-scale applications. In this paper, we present a fast, simple, yet effective m
Externí odkaz:
http://arxiv.org/abs/2407.11174
Local image feature descriptors have had a tremendous impact on the development and application of computer vision methods. It is therefore unsurprising that significant efforts are being made for learning-based image point descriptors. However, the
Externí odkaz:
http://arxiv.org/abs/2312.15471
In this paper, we showcase the effectiveness of optimizing monocular camera poses as a continuous function of time. The camera poses are represented using an implicit neural function which maps the given time to the corresponding camera pose. The map
Externí odkaz:
http://arxiv.org/abs/2311.17119
Modeling Neural Radiance Fields for fast-moving deformable objects from visual data alone is a challenging problem. A major issue arises due to the high deformation and low acquisition rates. To address this problem, we propose to use event cameras t
Externí odkaz:
http://arxiv.org/abs/2309.08416
The essence of video semantic segmentation (VSS) is how to leverage temporal information for prediction. Previous efforts are mainly devoted to developing new techniques to calculate the cross-frame affinities such as optical flow and attention. Inst
Externí odkaz:
http://arxiv.org/abs/2207.10436
Implicit fields have recently shown increasing success in representing and learning 3D shapes accurately. Signed distance fields and occupancy fields are decades old and still the preferred representations, both with well-studied properties, despite
Externí odkaz:
http://arxiv.org/abs/2204.06552
Boundaries are among the primary visual cues used by human and computer vision systems. One of the key problems in boundary detection is the label representation, which typically leads to class imbalance and, as a consequence, to thick boundaries tha
Externí odkaz:
http://arxiv.org/abs/2203.08795
Efficient detection and description of geometric regions in images is a prerequisite in visual systems for localization and mapping. Such systems still rely on traditional hand-crafted methods for efficient generation of lightweight descriptors, a co
Externí odkaz:
http://arxiv.org/abs/2203.03610
Autor:
Gong, Rui, Danelljan, Martin, Dai, Dengxin, Paudel, Danda Pani, Chhatkuli, Ajad, Yu, Fisher, Van Gool, Luc
Traditional 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 domai
Externí odkaz:
http://arxiv.org/abs/2109.04813
This paper tackles the high computational/space complexity associated with Multi-Head Self-Attention (MHSA) in vanilla vision transformers. To this end, we propose Hierarchical MHSA (H-MHSA), a novel approach that computes self-attention in a hierarc
Externí odkaz:
http://arxiv.org/abs/2106.03180