Text-to-image diffusion models have shown powerful ability on conditional image synthesis. With large-scale vision-language pre-training, diffusion models are able to generate high-quality images with rich textures and reasonable structures under different text prompts. However, adapting pre-trained diffusion models for visual perception is an open problem. In this paper, we propose an implicit and explicit language guidance framework for diffusion-based visual perception, named IEDP. Our IEDP comprises an implicit language guidance branch and an explicit language guidance branch. The implicit branch employs a frozen CLIP image encoder to directly generate implicit text embeddings that are fed to the diffusion model without explicit text prompts. The explicit branch uses the ground-truth labels of corresponding images as text prompts to condition feature extraction in diffusion model. During training, we jointly train the diffusion model by sharing the model weights of these two branches. As a result, the implicit and explicit branches can jointly guide feature learning. During inference, we employ only implicit branch for final prediction, which does not require any ground-truth labels. Experiments are performed on two typical perception tasks, including semantic segmentation and depth estimation. Our IEDP achieves promising performance on both tasks. For semantic segmentation, our IEDP has the mIoU$^\text{ss}$score of 55.9% on ADE20K validation set, which outperforms the baseline method VPD by 2.2%. For depth estimation, our IEDP outperforms the baseline method VPD with a relative gain of 11.0%.

The paper first proposes a method to correctly update the weights of an adaptive array antenna using the inherent processing gain of a spread spectrum (SS) receiver, even for received signals with very low desired-to-undesired signal power ratio (DUR). Since the method reduces effect of the delay in the controlling loop, stable convergence can be guaranteed in a fading channel. Secondly the method is applied to a tapped delay line (TDL) adaptive array antenna in order to improve performance of rejecting co-channel interference in CDMA. The array is investigated corresponding to the DUR and bandwidth of SS signals.>