The recent surge in large-scale foundation models has spurred the develo...
Physics-informed neural networks (PINNs) have recently emerged as promis...
Continuous convolution has recently gained prominence due to its ability...
Neural fields, also known as coordinate-based or implicit neural
represe...
Neural radiance fields (NeRF) have demonstrated the potential of
coordin...
Physics-informed neural networks (PINNs) have emerged as new data-driven...
With the increases in computational power and advances in machine learni...
Neural fields have emerged as a new data representation paradigm and hav...
Implicit neural representation (INR) has emerged as a powerful paradigm ...
We investigate using reinforcement learning agents as generative models ...
Computer vision has achieved impressive progress in recent years. Meanwh...
We propose to learn curvature information for better generalization and ...
The Low-Power Image Recognition Challenge (LPIRC,
https://rebootingcompu...
This paper improves state-of-the-art on-line trackers that use deep lear...
We present a transformation-grounded image generation network for novel ...
We present a new public dataset with a focus on simulating robotic visio...
In this paper, we introduce a new dataset consisting of 360,001 focused
...