3 accepted papers
Recent advances in skeleton-based action recognition have been primarily driven by Graph Convolutional Networks (GCNs) and skeleton transformers. While conventional approaches focus on modeling joint co-occurrences through skeletal connections, they overlook the inherent positional information in 3D
Generative Adversarial Networks (GANs) are often used in face sketch synthesis due to their powerful ability in image generation. However, most GAN based synthesis methods took the entire face as the minimum unit. Differently, we propose a novel fine-granularity face sketch synthesis framework in th…
Recently low-bit (e.g., 8-bit) network quantization has been extensively studied to accelerate the inference. Besides inference, low-bit training with quantized gradients can further bring more considerable acceleration, since the backward process is often computation-intensive. Unfortunately, the i…