Large language models have recently been shown to attain reasonable zero-shot generalization on a diverse set of tasks.
The input are an initial estimate of the point cloud and the camera parameters.
Multi-object tracking (MOT) aims at estimating bounding boxes and identities of objects in videos.
Ranked #1 on Multi-Object Tracking on MOT17 (using extra training data)
An approach to tackle this issue is to introduce Positional Encoding (PE) of nodes, and inject it into the input layer, like in Transformers.
We observe that despite their hierarchical convolutional nature, the synthesis process of typical generative adversarial networks depends on absolute pixel coordinates in an unhealthy manner.
Ranked #1 on Image Generation on FFHQ-U
We find that one of the main reasons for that is the lack of an effective receptive field in both the inpainting network and the loss function.