DivAvatar: Diverse 3D Avatar Generation with a Single Prompt

Text-to-Avatar generation has recently made significant strides due to advancements in diffusion models. However, most existing work remains constrained by limited diversity, producing avatars with subtle differences in appearance for a given text prompt. We design DivAvatar, a novel framework that generates diverse avatars, empowering 3D creatives with a multitude of distinct and richly varied 3D avatars from a single text prompt. Different from most existing work that exploits scene-specific 3D representations such as NeRF, DivAvatar finetunes a 3D generative model (i.e., EVA3D), allowing diverse avatar generation from simply noise sampling in inference time. DivAvatar has two key designs that help achieve generation diversity and visual quality. The first is a noise sampling technique during training phase which is critical in generating diverse appearances. The second is a semantic-aware zoom mechanism and a novel depth loss, the former producing appearances of high textual fidelity by separate fine-tuning of specific body parts and the latter improving geometry quality greatly by smoothing the generated mesh in the features space. Extensive experiments show that DivAvatar is highly versatile in generating avatars of diverse appearances

Mitigating Object Hallucinations in Large Vision-Language Models through Visual Contrastive Decoding

Large Vision-Language Models (LVLMs) have advanced considerably, intertwining visual recognition and language understanding to generate content that is not only coherent but also contextually attuned. Despite their success, LVLMs still suffer from the issue of object hallucinations, where models generate plausible yet incorrect outputs that include objects that do not exist in the images. To mitigate this issue, we introduce Visual Contrastive Decoding (VCD), a simple and training-free method that contrasts output distributions derived from original and distorted visual inputs. The proposed VCD effectively reduces the over-reliance on statistical bias and unimodal priors, two essential causes of object hallucinations. This adjustment ensures the generated content is closely grounded to visual inputs, resulting in contextually accurate outputs. Our experiments show that VCD, without either additional training or the usage of external tools, significantly mitigates the object hallucination issue across different LVLM families. Beyond mitigating object hallucinations, VCD also excels in general LVLM benchmarks, highlighting its wide-ranging applicability

Borrow from Source Models: Efficient Infrared Object Detection with Limited Examples

Recent deep models trained on large-scale RGB datasets lead to considerable achievements in visual detection tasks. However, the training examples are often limited for an infrared detection task, which may deteriorate the performance of deep detectors. In this paper, we propose a transfer approach, Source Model Guidance (SMG), where we leverage a high-capacity RGB detection model as the guidance to supervise the training process of an infrared detection network. In SMG, the foreground soft label generated from the RGB model is introduced as source knowledge to provide guidance for cross-domain transfer. Additionally, we design a Background Suppression Module in the infrared network to receive the knowledge and enhance the foreground features. SMG is easily plugged into any modern detection framework, and we show two explicit instantiations of it, SMG-C and SMG-Y, based on CenterNet and YOLOv3, respectively. Extensive experiments on different benchmarks show that both SMG-C and SMG-Y achieve remarkable performance even if the training set is scarce. Compared to advanced detectors on public FLIR, SMG-Y with 77.0% mAP outperforms others in accuracy, and SMG-C achieves real-time detection at a speed of 107 FPS. More importantly, SMG-Y trained on a quarter of the thermal dataset obtains 74.5% mAP, surpassing most state-of-the-art detectors with full FLIR as training data

Kinetics of Phosphorus Transfer during Industrial Electroslag Remelting of G20CrNi2Mo Bearing Steel

Phosphorus is undesirable in steel for it greatly decreases ductility and causes embrittlement in most cases. The kinetic behavior of phosphorus transfer was investigated during electroslag remelting (ESR) of G20CrNi2Mo bearing steel. Four heat treatments were carried out using an industrial furnace with a capacity to refine 2400 kg ingot. It was found the P content in the four ingots were all higher than that in the electrodes, indicating rephosphorization occurs during ESR. A kinetic model based on film and penetration theory was developed to elucidate the variation of phosphorus from metal film to droplet and metal pool. The model indicates that the rate-determining step of phosphorus transfer is at the slag side. Rephosphorization mainly occurs in the metal film and falling droplet. In addition, the effect of P in the slag and electrode, as well as the temperature of the slag pool on the P content in the metal pool were discussed. In order to achieve a low-P ingot of no more than 0.015%, the corresponding maximum P content in slag under the condition of a certain P content in the electrode was proposed

Apoptosis-Promoting Effects of Hematoporphyrin Monomethyl Ether-Sonodynamic Therapy (HMME-SDT) on Endometrial Cancer

<div><p>Objective</p><p>The aim of the present study was to examine the apoptosis-promoting effects and mechanisms of hematoporphyrin monomethyl ether (HMME)-sonodynamic therapy (SDT) on endometrial cancer cells <i>in vitro</i>.</p><p>Methods</p><p>Endometrial cancer cell samples were divided into four groups: 1) untreated control group, 2) HMME group, 3) pure ultrasound group, and 4) HMME combined with ultrasound, i.e. SDT group. CCK-8 method was utilized to assess the inhibiting effect of SDT on the proliferation of endometrial cancer cells. Optical microscope and field emission transmission electron microscopy were used to characterize the morphology changes of the cancer cells induced by the treatments. Apoptosis rate, reactive oxygen species (ROS) and mitochondrial membrane potential (MMP) were examined by flow cytometer. Fluorescence intensity measured by laser scanning confocal microscopy was used to explore the variation of intracellular calcium ion (Ca²⁺) concentration. Apoptosis-related proteins involved in both intrinsic and extrinsic apoptosis signallings were analyzed by western blot.</p><p>Results</p><p>SDT can effectively induce the apoptosis of endometrial cancer cells. Compared with ultrasound which is known as an effective anti-tumor method, SDT leads to a significant improvement on suppression of cell viability and induction of apoptosis, together with more remarkable modifications on the morphology and substructure in both ultrasound sensitive and resistant endometrial cancer cells. Further studies reveals that SDT promotes ROS production, induces loss of MMP and increases intracellular Ca²⁺ concentration more efficiently than HMME or ultrasound alone. SDT groups also show a rather high expression of apoptosis-promoting proteins, including Bax, Fas and Fas-L, and a significant low expression of apoptosis-suspending proteins including Bcl-2 and Survivin. Meanwhile, both cleaved caspse-3 and caspase-8 are dramatically enhanced in SDT groups. Multiple pathways has been proposed in the process, including the intrinsic activation by excessive ROS and overloaded Ca²⁺, silencing survivin gene, and the extrinsic pathway mediated by the death receptor.</p><p>Conclusion</p><p>Given its considerable effectivity in both ultrasound sensitive and resistant cells, SDT may therefore be a promising therapeutic method for treating endometrial cancers.</p></div

Effect of SDT on the expression of apoptotic-related proteins by western blot.

<p>Ishikawa (a) and HEC-1-a (b) were subjected to four different treatments: control, HMME, ultrasound and SDT. Apoptosis related markers were detected by Western blotting with specific antibodies as indicated. β-actin was used a loading control.</p

Effect of SDT on the MMP reduction in endometrial cancer cells.

<p>Ishikawa (a and b) and HEC-1-a (c and d) were subjected to four different treatments: control, HMME, ultrasound and SDT. Loss of MMP was more evident in SDT group than the other groups. Representative FACS profiles were shown in a and c. Histograms present mean ± SD of three independent experiments (b and d, ** P < 0.01.)</p