Abstract Maintaining human body temperature is one of the basic needs for living, which requires high‐performance thermal insulation materials to prevent heat exchange with external environment. However, most widely used fibrous always suffer from heavy weight, weak mechanical property, and moderate capacity suppress transfer, resulting in limited personal cold protection performance. Here, an ultralight, mechanically robust, thermally insulating polyimide (PI) aerogel directly synthesized...

Abstract Extreme cold events are becoming more frequent and intense around the world, imposing a huge burden on human health global economy. However, developing fibrous materials featuring ultralight weight, high shape retention, thermal insulation to withstand extreme conditions remains great challenge. Herein, inspired by natural porous loofah, an superelastic micro/nanofibrous aerogel (MNFA) that integrates hierarchical pores stable physical entanglements is directly synthesized via...

The problem of cross-modality person re-identification has been receiving increasing attention recently, due to its practical significance. Motivated by the fact that human usually attend difference when they compare two similar objects, we propose a dual-path feature learning framework which preserves intrinsic spatial structures and attends input image pairs. Our is composed main components: Dual-path Spatial-structure-preserving Common Space Network (DSCSN) Contrastive Correlation (CCN)....

With the emergence of large pre-trained vison-language model like CLIP, transferable representations can be adapted to a wide range downstream tasks via prompt tuning. Prompt tuning tries probe beneficial information for from general knowledge stored in model. A recently proposed method named Context Optimization (CoOp) introduces set learnable vectors as text language side. However, alone only adjust synthesized "classifier", while computed visual features image encoder not affected , thus...

<title>Abstract</title> The temporal dynamics of phage-host interactions within full-scale biological wastewater treatment (BWT) plants remain inadequately characterized. Here, we provide an in-depth investigation viral and bacterial over a nine-year period in activated sludge BWT plant, where bleach addition was applied to control foaming. By conducting bioinformatic analyses on 98 metagenomic time-series samples, reconstructed 3,486 genomes 2,435 complete or near-complete genomes, which...

This article investigates the problem of continual learning (CL) vision-language models (VLMs) in open domains, where are required to perform updating and inference on a stream datasets from diverse seen unseen domains with novel classes. Such capability is crucial for various applications environments, e.g., AI assistants, autonomous driving systems, robotics. Current CL studies mostly focus closed-set scenarios single domain known Large pretrained VLMs such as CLIP have showcased...

A critical challenge for multi-modal Object Re-Identification (ReID) is the effective aggregation of complementary information to mitigate illumination issues. State-of-the-art methods typically employ complex and highly-coupled architectures, which unavoidably result in heavy computational costs. Moreover, significant distribution gap among different image spectra hinders joint representation multimodal features. In this paper, we propose a framework named as PromptMA establish...

Modeling the relationship among human joints is one of most important components in pose estimation. Most previous methods define this as a geometric constraint on relative locations two neighboring joints. In constraint, local appearance region connecting ignored. However, discarding image leads to some severe problems, such double-counting and localization failure when rare training dataset. Moreover, appearance, called limb, plays an role estimation visual system. Due these reasons, we...

Semantic segmentation is an important and popular research area in computer vision that focuses on classifying pixels image based their semantics. However, supervised deep learning requires large amounts of data to train models the process labeling images pixel by time-consuming laborious. This review aims provide a first comprehensive organized overview state-of-the-art results pseudo-label methods field semi-supervised semantic segmentation, which we categorize from different perspectives...

To imitate the ability of keeping learning human, continual which can learn from a never-ending data stream has attracted more interests recently. In all settings, online class incremental (OCIL), where incoming samples be used only once, is challenging and encountered frequently in real world. Actually, models face stability-plasticity dilemma, stability means to preserve old knowledge while plasticity denotes incorporate new knowledge. Although replay-based methods have shown exceptional...

Cross-view person identification (CVPI) from multiple temporally synchronized videos taken by wearable cameras different, varying views is a very challenging but important problem, which has attracted more interest recently. Current state-of-the-art performance of CVPI achieved matching appearance and motion features across videos, while the pose does not work effectively given high inaccuracy 3D estimation on videos/images collected in wild. To address this we first introduce new metric...

Finding target persons in full scene images with a query of text description has important practical applications intelligent video surveillance. However, different from the real-world scenarios where bounding boxes are not available, existing text-based person re- trieval methods mainly focus on cross modal matching between descriptions and gallery cropped pedestrian images. To close gap, we study problem search by proposing new end-to-end learning framework which jointly optimize...

Camouflaged object detection (COD) aims to segment camouflaged objects which exhibit very similar patterns with the surrounding environment. Recent research works have shown that enhancing feature representation via frequency information can greatly alleviate ambiguity problem between foreground and background.With emergence of vision foundation models, like InternImage, Segment Anything Model etc, adapting pretrained model on COD tasks a lightweight adapter module shows novel promising...

Cross-view person identification (CVPI) from multiple temporally synchronized videos taken by wearable cameras different, varying views is a very challenging but important problem, which has attracted more interests recently. Current state-of-the-art performance of CVPI achieved matching appearance and motion features across videos, while the pose does not work effectively given high inaccuracy 3D human estimation on videos/images collected in wild. In this paper, we introduce new metric...

In this work, we construct a large-scale dataset for Ground-to-Aerial Person Search, named G2APS, which contains 31,770 images of 260,559 annotated bounding boxes 2,644 identities appearing in both the UAVs and ground surveillance cameras. To our knowledge, is first cross-platform intelligent applications, where could work as powerful complement more realistically simulate actual scenarios, cameras are fixed about 2 meters above ground, while capture videos persons at different location,...