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pro vyhledávání: '"Chen, Xuanyao"'
High-resolution images enable neural networks to learn richer visual representations. However, this improved performance comes at the cost of growing computational complexity, hindering their usage in latency-sensitive applications. As not all pixels
Externí odkaz:
http://arxiv.org/abs/2303.17605
Perception and prediction are two separate modules in the existing autonomous driving systems. They interact with each other via hand-picked features such as agent bounding boxes and trajectories. Due to this separation, prediction, as a downstream m
Externí odkaz:
http://arxiv.org/abs/2208.01582
Accurate and consistent 3D tracking from multiple cameras is a key component in a vision-based autonomous driving system. It involves modeling 3D dynamic objects in complex scenes across multiple cameras. This problem is inherently challenging due to
Externí odkaz:
http://arxiv.org/abs/2205.00613
Publikováno v:
CVPR 2023 workshop on autonomous driving
Sensor fusion is an essential topic in many perception systems, such as autonomous driving and robotics. Existing multi-modal 3D detection models usually involve customized designs depending on the sensor combinations or setups. In this work, we prop
Externí odkaz:
http://arxiv.org/abs/2203.10642
The world provides us with data of multiple modalities. Intuitively, models fusing data from different modalities outperform their uni-modal counterparts, since more information is aggregated. Recently, joining the success of deep learning, there is
Externí odkaz:
http://arxiv.org/abs/2106.04538