Neural Architecture Search (NAS) aims to automatically excavate the opti...
This paper analyses the design choices of face detection architecture th...
Trainable layers such as convolutional building blocks are the standard
...
Image-mixing augmentations (e.g., Mixup or CutMix), which typically mix ...
Recent weakly-supervised semantic segmentation (WSSS) has made remarkabl...
We propose a novel and effective input transformation based adversarial
...
We consider a class-incremental semantic segmentation (CISS) problem. Wh...
Continual learning is a realistic learning scenario for AI models. Preva...
In this paper, a new method of training pipeline is discussed to achieve...
This paper addresses representational bottleneck in a network and propos...
The cost of labeling transcriptions for large speech corpora becomes a
b...
This paper studies the scratch training of quantization-aware training (...
Despite apparent human-level performances of deep neural networks (DNN),...
Designing a lightweight and robust portrait segmentation algorithm is an...
We propose a generic confidence-based approximation that can be plugged ...
This paper proposes a new high dimensional regression method by merging
...
Designing a lightweight and robust portrait segmentation algorithm is an...
In this paper, we propose a new multi-scale face detector having an extr...
Regional dropout strategies have been proposed to enhance the performanc...
The semantic segmentation requires a lot of computational cost. The dila...
In this paper, we introduce a new method for generating an object image ...
This paper proposes a new algorithm for controlling classification resul...
In this work, we introduce a new algorithm for analyzing a diagram, whic...
This paper proposes a novel deep reinforcement learning (RL) method
inte...
Semantic segmentation, like other fields of computer vision, has seen a
...