While only the semantics of each task differ, current research focuses on designing specialized architectures for each task.
Ranked #1 on Panoptic Segmentation on COCO minival
In this work, we introduce this approach into the realm of encoder-based inversion.
Ranked #1 on Fine-tuning on 2021 Hotel-ID
A reverse dictionary takes descriptions of words as input and outputs words semantically matching the input descriptions.
We introduce a prototype model and provide an open-source and extensible toolkit called OpenUE for various extraction tasks.
Due to the complex nature of this multimodal task, which combines text reasoning, video understanding, instance segmentation and tracking, existing approaches typically rely on sophisticated pipelines in order to tackle it.
Ranked #1 on Referring Expression Segmentation on A2D Sentences
Long-tailed relation classification is a challenging problem as the head classes may dominate the training phase, thereby leading to the deterioration of the tail performance.
Moving from data to latent space allows us to train more expressive generative models, apply SGMs to non-continuous data, and learn smoother SGMs in a smaller space, resulting in fewer network evaluations and faster sampling.
Ranked #1 on Image Generation on CIFAR-10
Malware family classification is a significant issue with public safety and research implications that has been hindered by the high cost of expert labels.