Effective Real Image Editing with Accelerated Iterative Diffusion Inversion

Despite all recent progress, it is still challenging to edit and manipulate natural images with modern generative models. When using Generative Adversarial Network (GAN), one major hurdle is in the inversion process mapping a real image to its corresponding noise vector in the latent space, since its necessary to be able to reconstruct an image to edit its contents. Likewise for Denoising Diffusion Implicit Models (DDIM), the linearization assumption in each inversion step makes the whole deterministic inversion process unreliable. Existing approaches that have tackled the problem of inversion stability often incur in significant trade-offs in computational efficiency. In this work we propose an Accelerated Iterative Diffusion Inversion method, dubbed AIDI, that significantly improves reconstruction accuracy with minimal additional overhead in space and time complexity. By using a novel blended guidance technique, we show that effective results can be obtained on a large range of image editing tasks without large classifier-free guidance in inversion. Furthermore, when compared with other diffusion inversion based works, our proposed process is shown to be more robust for fast image editing in the 10 and 20 diffusion steps' regimes.Comment: Accepted to ICCV 2023 (Oral

HollowNeRF: Pruning Hashgrid-Based NeRFs with Trainable Collision Mitigation

Neural radiance fields (NeRF) have garnered significant attention, with recent works such as Instant-NGP accelerating NeRF training and evaluation through a combination of hashgrid-based positional encoding and neural networks. However, effectively leveraging the spatial sparsity of 3D scenes remains a challenge. To cull away unnecessary regions of the feature grid, existing solutions rely on prior knowledge of object shape or periodically estimate object shape during training by repeated model evaluations, which are costly and wasteful. To address this issue, we propose HollowNeRF, a novel compression solution for hashgrid-based NeRF which automatically sparsifies the feature grid during the training phase. Instead of directly compressing dense features, HollowNeRF trains a coarse 3D saliency mask that guides efficient feature pruning, and employs an alternating direction method of multipliers (ADMM) pruner to sparsify the 3D saliency mask during training. By exploiting the sparsity in the 3D scene to redistribute hash collisions, HollowNeRF improves rendering quality while using a fraction of the parameters of comparable state-of-the-art solutions, leading to a better cost-accuracy trade-off. Our method delivers comparable rendering quality to Instant-NGP, while utilizing just 31% of the parameters. In addition, our solution can achieve a PSNR accuracy gain of up to 1dB using only 56% of the parameters.Comment: Accepted to ICCV 202

AutoShot: A Short Video Dataset and State-of-the-Art Shot Boundary Detection

The short-form videos have explosive popularity and have dominated the new social media trends. Prevailing short-video platforms,~\textit{e.g.}, Kuaishou (Kwai), TikTok, Instagram Reels, and YouTube Shorts, have changed the way we consume and create content. For video content creation and understanding, the shot boundary detection (SBD) is one of the most essential components in various scenarios. In this work, we release a new public Short video sHot bOundary deTection dataset, named SHOT, consisting of 853 complete short videos and 11,606 shot annotations, with 2,716 high quality shot boundary annotations in 200 test videos. Leveraging this new data wealth, we propose to optimize the model design for video SBD, by conducting neural architecture search in a search space encapsulating various advanced 3D ConvNets and Transformers. Our proposed approach, named AutoShot, achieves higher F1 scores than previous state-of-the-art approaches, e.g., outperforming TransNetV2 by 4.2%, when being derived and evaluated on our newly constructed SHOT dataset. Moreover, to validate the generalizability of the AutoShot architecture, we directly evaluate it on another three public datasets: ClipShots, BBC and RAI, and the F1 scores of AutoShot outperform previous state-of-the-art approaches by 1.1%, 0.9% and 1.2%, respectively. The SHOT dataset and code can be found in https://github.com/wentaozhu/AutoShot.git .Comment: 10 pages, 5 figures, 3 tables, in CVPR 2023; Top-1 solution for scene / shot boundary detection https://paperswithcode.com/paper/autoshot-a-short-video-dataset-and-state-o

Influence of Intrinsic Electronic Properties on Light Transmission through Subwavelength Holes on Gold and MgB2 Thin Films

We show how intrinsic material properties modify light transmission through subwavelength hole arrays on thin metallic films in the THz regime. We compare the temperature-dependent transmittance of Au films and MgB$_{2}$ films. The experimental data is consistent with analytical calculations, and is attributed to the temperature change of the conductivity of both films. The transmission versus conductivity is interpreted within the open resonator model when taking the skin depth into consideration. We also show that the efficiency of this temperature control depends on the ratio of the transmission peak frequency to the superconducting energy gap in MgB$_{2}$ films.Comment: 6 pages, 6 figure

The transcriptional coactivator TAZ regulates reciprocal differentiation of T(h)17 cells and T(reg) cells

自身免疫性疾病是一类机体对自身抗原发生免疫反应而导致自身多器官、组织受累的慢性炎症性疾病。目前大量研究表明机体内促炎症的TH17细胞和抑制炎症Treg细胞在类群数量和活化状态的失衡是造成自身免疫疾病的主要致病因素。陈兰芬教授和周大旺教授团队的前期研究发现小鼠中Hippo信号通路中激酶Mst1/2缺失导致免疫缺陷，机体易受病原体感染并伴随着严重自身免疫疾病。该研究揭示了Hippo 信号通路转录共激活因子TAZ在决定CD4+初始T细胞分化为促进炎症的TH17效应细胞和抑制免疫反应的Treg调节性细胞过程中发挥着关键作用，拓展了当前对于Hippo信号通路的相关研究内容。 陈兰芬，博士，厦门大学生命科学学院教授。【Abstraact】An imbalance in the lineages of immunosuppressive regulatory T cells (Treg cells) and the inflammatory TH17 subset of helper T cells leads to the development of autoimmune and/or inflammatory disease. Here we found that TAZ, a coactivator of TEAD transcription factors of Hippo signaling, was expressed under T H17 cell–inducing conditions and was required for TH17 differentiation and TH17 cell–mediated inflammatory diseases. TAZ was a critical co-activator of the TH17-defining transcription factor RORγt. In addition, TAZ attenuated Treg cell development by decreasing acetylation of the Treg cell master regulator Foxp3 mediated by the histone acetyltransferase Tip60, which targeted Foxp3 for proteasomal degradation. In contrast, under T regcell–skewing conditions, TEAD1 expression and sequestration of TAZ from the transcription factors RORγt and Foxp3 promoted Treg cell differentiation. Furthermore, deficiency in TAZ or overexpression of TEAD1 induced Treg cell differentiation, whereas expression of a transgene encoding TAZ or activation of TAZ directed TH17 cell differentiation. Our results demonstrate a pivotal role for TAZ in regulating the differentiation of Treg cells and TH17 cells.J. Avruch for comments on the manuscript.Supported by the National Basic Research Program (973) of China (2015CB910502 to L.C.), the National Natural Science Foundation of China (81422018 to L.C.; 31625010 and U1505224 to D.Z.; U1405225 and 81372617 to L.C.; J1310027 to D.Z.; 81472229 to L.H.; and 31600698 to J. Geng), the 111 Projects (B12001 and B06016), China's 1000 Young Talents Program (D.Z., and L.C.), the Fundamental Research Funds for the Central Universities of China-Xiamen University (20720160071 to D.Z. and 20720160054 to L.H.) and Major disease research projects of Xiamen (3502Z20149029 to L.C.)

Ceramides and metabolic profiles of patients with acute coronary disease: a cross-sectional study

Metabolic Syndrome (MS) is a rapidly growing medical problem worldwide and is characterized by a cluster of age-related metabolic risk factors. The presence of MS increases the likelihood of developing atherosclerosis and significantly raises the morbidity/mortality rate of acute coronary syndrome (ACS) patients. Early detection of MS is crucial, and biomarkers, particularly blood-based, play a vital role in this process. This cross-sectional study focused on the investigation of certain plasma ceramides (Cer14:0, Cer16:0, Cer18:0, Cer20:0, Cer22:0, and Cer24:1) as potential blood biomarkers for MS due to their previously documented dysregulated function in MS patients. A total of 695 ACS patients were enrolled, with 286 diagnosed with MS (ACS-MS) and 409 without MS (ACS-nonMS) serving as the control group. Plasma ceramide concentrations were measured by LC-MS/MS assay and analyzed through various statistical methods. The results revealed that Cer18:0, Cer20:0, Cer22:0, and Cer24:1 were significantly correlated with the presence of MS risk factors. Upon further examination, Cer18:0 emerged as a promising biomarker for early MS detection and risk stratification, as its plasma concentration showed a significant sensitivity to minor changes in MS risk status in participants. This cross-sectional observational study was a secondary analysis of a multicenter prospective observational cohort study (Chinese Clinical Trial Registry, https://www.who.int/clinical-trials-registry-platform/network/primary-registries/chinese-clinical-trial-registry-(chictr), ChiCTR-2200056697), conducted from April 2021 to August 2022

A Conscious Resting State fMRI Study in SLE Patients Without Major Neuropsychiatric Manifestations

Neuropsychiatric systemic lupus erythematosus (NPSLE) is one of the main causes of death in patients with systemic lupus erythematosus (SLE). Signs and symptoms of NPSLE are heterogeneous, and it is hard to diagnose, and treat NPSLE patients in the early stage. We conducted this study to explore the possible brain activity changes using resting state functional magnetic resonance imaging (rs-fMRI) in SLE patients without major neuropsychiatric manifestations (non-NPSLE patients). We also tried to investigate the possible associations among brain activity, disease activity, depression, and anxiety. In our study, 118 non-NPSLE patients and 81 healthy controls (HC) were recruited. Rs-fMRI data were used to calculate the regional homogeneity (ReHo) in all participants. We found decreased ReHo values in the fusiform gyrus and thalamus and increased ReHo values in the parahippocampal gyrus and uncus. The disease activity was positively correlated with ReHo values of the cerebellum and negatively correlated with values in the frontal gyrus. Several brain areas showed correlations with depressive and anxiety statuses. These results suggested that abnormal brain activities might occur before NPSLE and might be the foundation of anxiety and depression symptoms. Early detection and proper treatment of brain dysfunction might prevent the progression to NPSLE. More studies are needed to understand the complicated underlying mechanisms