CM-GAN: Image Inpainting with Cascaded Modulation GAN and Object-Aware Training

Recent image inpainting methods have made great progress but often struggle to generate plausible image structures when dealing with large holes in complex images. This is partially due to the lack of effective network structures that can capture both the long-range dependency and high-level semantics of an image. To address these problems, we propose cascaded modulation GAN (CM-GAN), a new network design consisting of an encoder with Fourier convolution blocks that extract multi-scale feature representations from the input image with holes and a StyleGAN-like decoder with a novel cascaded global-spatial modulation block at each scale level. In each decoder block, global modulation is first applied to perform coarse semantic-aware structure synthesis, then spatial modulation is applied on the output of global modulation to further adjust the feature map in a spatially adaptive fashion. In addition, we design an object-aware training scheme to prevent the network from hallucinating new objects inside holes, fulfilling the needs of object removal tasks in real-world scenarios. Extensive experiments are conducted to show that our method significantly outperforms existing methods in both quantitative and qualitative evaluation.Comment: 32 pages, 18 figure

Structure-Guided Image Completion with Image-level and Object-level Semantic Discriminators

Structure-guided image completion aims to inpaint a local region of an image according to an input guidance map from users. While such a task enables many practical applications for interactive editing, existing methods often struggle to hallucinate realistic object instances in complex natural scenes. Such a limitation is partially due to the lack of semantic-level constraints inside the hole region as well as the lack of a mechanism to enforce realistic object generation. In this work, we propose a learning paradigm that consists of semantic discriminators and object-level discriminators for improving the generation of complex semantics and objects. Specifically, the semantic discriminators leverage pretrained visual features to improve the realism of the generated visual concepts. Moreover, the object-level discriminators take aligned instances as inputs to enforce the realism of individual objects. Our proposed scheme significantly improves the generation quality and achieves state-of-the-art results on various tasks, including segmentation-guided completion, edge-guided manipulation and panoptically-guided manipulation on Places2 datasets. Furthermore, our trained model is flexible and can support multiple editing use cases, such as object insertion, replacement, removal and standard inpainting. In particular, our trained model combined with a novel automatic image completion pipeline achieves state-of-the-art results on the standard inpainting task.Comment: 18 pages, 16 figure

Comprehensive characterization of ERV-K (HML-8) in the chimpanzee genome revealed less genomic activity than humans

Endogenous retroviruses (ERVs) originate from ancestral germline infections caused by exogenous retroviruses. Throughout evolution, they have become fixed within the genome of the animals into which they were integrated. As ERV elements coevolve with the host, they are normally epigenetically silenced and can become upregulated in a series of physiological and pathological processes. Generally, a detailed ERV profile in the host genome is critical for understanding the evolutionary history and functional performance of the host genome. We previously characterized and cataloged all the ERV-K subtype HML-8 loci in the human genome; however, this has not been done for the chimpanzee, the nearest living relative of humans. In this study, we aimed to catalog and characterize the integration of HML-8 in the chimpanzee genome and compare it with the integration of HML-8 in the human genome. We analyzed the integration of HML-8 and found that HML-8 pervasively invaded the chimpanzee genome. A total of 76 proviral elements were characterized on 23/24 chromosomes, including detailed elements distribution, structure, phylogeny, integration time, and their potential to regulate adjacent genes. The incomplete structure of HML-8 proviral LTRs will undoubtedly affect their activity. Moreover, the results indicated that HML-8 integration occurred before the divergence between humans and chimpanzees. Furthermore, chimpanzees include more HML-8 proviral elements (76 vs. 40) and fewer solo long terminal repeats (LTR) (0 vs. 5) than humans. These results suggested that chimpanzee genome activity is less than the human genome and that humans may have a better ability to shape and screen integrated proviral elements. Our work is informative in both an evolutionary and a functional context for ERVs

Identification of differentially expressed HERV-K(HML-2) loci in colorectal cancer

Colorectal cancer is one of the malignant tumors with the highest mortality rate in the world. Survival rates vary significantly among patients at various stages of the disease. A biomarker capable of early diagnosis is required to facilitate the early detection and treatment of colorectal cancer. Human endogenous retroviruses (HERVs) are abnormally expressed in various diseases, including cancer, and have been involved in cancer development. Real-time quantitative PCR was used to detect the transcript levels of HERV-K(HML-2) gag, pol, and env in colorectal cancer to systematically investigate the connection between HERV-K(HML-2) and colorectal cancer. The results showed that HERV-K(HML-2) transcript expression was significantly higher than healthy controls and was consistent at the population and cell levels. We also used next-generation sequencing to identify and characterize HERV-K(HML-2) loci that were differentially expressed between colorectal cancer patients and healthy individuals. The analysis revealed that these loci were concentrated in immune response signaling pathways, implying that HERV-K impacts the tumor-associated immune response. Our results indicated that HERV-K might serve as a screening tumor marker and a target for tumor immunotherapy in colorectal cancer

Measurement, Distribution Characteristics, and Convergent Analysis of China’s Green Development Level

In order to carry out the concept of harmonious coexistence between man and nature, a multi-level national green development evaluation index system referenced to the relevant data of the provinces and a measurable model were constructed, and the green development level of each province in China was measured as an example. Meanwhile, the distribution and form characteristics and the regional differences between the green development levels of each province were estimated and analyzed through the nuclear density function and dagum Gini coefficient. The results indicate that some provinces and cities in China are concentrated at the backward level in the green development level and its sub-evaluation dimension, and a few first-line provinces and cities are developed; The largest contribution rate of regional differences is the main causation of regional differences, the comprehensive evaluation score of green development level in the whole country and the eastern region is σ-convergent, while there is no σ-convergence in the central and western region; The green development level of the whole country and the three parts of the east, central and western China is β-convergent and converges at the same steady-state level respectively