We present a novel music generation framework for music infilling, with a user friendly interface.
Our model learns to camouflage a variety of object shapes from randomly sampled locations and viewpoints within the input scene, and is the first to address the problem of hiding complex object shapes.
In this paper, we introduce a novel approach that integrates uncertainty-aware spatiotemporal graph learning and model-based state estimation for a team of robots to collaboratively localize objects.
no code implementations • 3 Mar 2021 • Zhu Liu, Zhu Deng, Philippe Ciais, Jianguang Tan, Biqing Zhu, Steven J. Davis, Robbie Andrew, Olivier Boucher, Simon Ben Arous, Pep Canadel, Xinyu Dou, Pierre Friedlingstein, Pierre Gentine, Rui Guo, Chaopeng Hong, Robert B. Jackson, Daniel M. Kammen, Piyu Ke, Corinne Le Quere, Crippa Monica, Greet Janssens-Maenhout, Glen Peters, Katsumasa Tanaka, Yilong Wang, Bo Zheng, Haiwang Zhong, Taochun Sun, Hans Joachim Schellnhuber
That even substantial world-wide lockdowns of activity led to a one-time decline in global CO$_2$ emissions of only 5. 4% in one year highlights the significant challenges for climate change mitigation that we face in the post-COVID era.
Atmospheric and Oceanic Physics General Economics Economics
In this paper, we examine the requirements, limitations, and performance of different cooperative perception techniques, and present an in-depth analysis of the notion of Deep Feature Sharing (DFS).
Collaborative object localization aims to collaboratively estimate locations of objects observed from multiple views or perspectives, which is a critical ability for multi-agent systems such as connected vehicles.
Many of the music generation systems based on neural networks are fully autonomous and do not offer control over the generation process.
Sound Symbolic Computation Audio and Speech Processing
The recent advancements in communication and computational systems has led to significant improvement of situational awareness in connected and autonomous vehicles.
The ability to model and predict ego-vehicle's surrounding traffic is crucial for autonomous pilots and intelligent driver-assistance systems.
We present a Python library, called Midi Miner, that can calculate tonal tension and classify different tracks.
Current VHR(Very High Resolution) satellite images enable the detailed monitoring of the earth and can capture the ongoing works of railway construction.
SIGNet is shown to improve upon the state-of-the-art unsupervised learning for depth prediction by 30% (in squared relative error).
Ranked #34 on Monocular Depth Estimation on KITTI Eigen split
In this paper, we propose a framework to reconstruct the 3D models by the multi-view point cloud registration algorithm with adaptive convergence threshold, and subsequently apply it to 3D model retrieval.
The data fidelity term in the MRF's energy function is jointly computed according to the superpixel features of color, texture and location.
With the overlapping percentage available, it views the overlapping percentage as the corresponding weight of each scan pair and proposes the weight motion averaging algorithm, which can pay more attention to reliable and accurate relative motions.
Among these parameters, visual and step are very significant in view of the fact that artificial fish basically move based on these parameters.