95 citations · 525 across the 28 of their papers we have counts for
7 papers · 1 filter
StyleSwin: Transformer-based GAN for High-resolution Image Generation
Bowen Zhang, Shuyang Gu, Bo Zhang +5
Despite the tantalizing success in a broad of vision tasks, transformers have not yet demonstrated on-par ability as ConvNets in high-resolution image generative modeling. In this…
Vector Quantized Diffusion Model for Text-to-Image Synthesis
Shuyang Gu, Dong Chen, Jianmin Bao +5
We present the vector quantized diffusion (VQ-Diffusion) model for text-to-image generation. This method is based on a vector quantized variational autoencoder (VQ-VAE) whose laten…
Robust Mutual Learning for Semi-supervised Semantic Segmentation
Pan Zhang, Bo Zhang, Ting Zhang +2
Recent semi-supervised learning (SSL) methods are commonly based on pseudo labeling. Since the SSL performance is greatly influenced by the quality of pseudo labels, mutual learnin…
Microshift: An Efficient Image Compression Algorithm for Hardware
Bo Zhang, Pedro V. Sander, Chi-Ying Tsui +1
In this paper, we propose an image compression algorithm called Microshift. We employ an algorithm hardware co-design methodology, yielding a hardware-friendly compression approach…
Let's See Clearly: Contaminant Artifact Removal for Moving Cameras
Xiaoyu Li, Bo Zhang, Jing Liao +1
Contaminants such as dust, dirt and moisture adhering to the camera lens can greatly affect the quality and clarity of the resulting image or video. In this paper, we propose a vid…
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
Chulin Xie, Chuxin Wang, Bo Zhang +3
In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion. Firstly, we present the channel-attentive EdgeConv…
Prototypical Pseudo Label Denoising and Target Structure Learning for Domain Adaptive Semantic Segmentation
Pan Zhang, Bo Zhang, Ting Zhang +3
Self-training is a competitive approach in domain adaptive segmentation, which trains the network with the pseudo labels on the target domain. However inevitably, the pseudo labels…