The missing modality issue is critical but non-trivial to be solved by multi-modal models. Current methods aiming handle the problem in tasks, either deal with modalities only during evaluation or train separate models specific settings. In addition, these are designed for so example, classification not easily adapted segmentation tasks and vice versa. this paper, we propose Shared-Specific Feature Modelling (ShaSpec) method that considerably simpler more effective than competing approaches...

Recently, with the rise of high dynamic range (HDR) display devices, there is a great demand to transfer traditional low (LDR) images into HDR versions. The key success how solve many-to-many mapping problem. However, existing approaches either do not consider constraining solution space or just simply imitate inverse camera imaging pipeline in stages, without directly formulating image generation process. In this work, we address problem by integrating LDR-to-HDR knowledge an UNet...

The costly and time-consuming annotation process to produce large training sets for modelling semantic LiDAR segmentation methods has motivated the development of semi-supervised learning (SSL) methods. However, such SSL approaches often concentrate on employing consistency only individual representations. This narrow focus results in limited perturbations that generally fail enable effective learning. Additionally, these employ contrastive based sampling from a set positive negative...

Audio-visual segmentation (AVS) is an emerging task that aims to accurately segment sounding objects based on audio-visual cues. The success of AVS learning systems depends the effectiveness cross-modal interaction. Such a requirement can be naturally fulfilled by leveraging transformer-based architecture due its inherent ability capture long-range dependencies and flexibility in handling different modalities. However, training issues methods, such as low efficacy cross-attention unstable...

Automatic lecture recording is an appealing alternative approach to manually lectures in the process of online course making as it can a large extent save labor cost. The key automatic system lecturer tracking, and existing tracking methods tend lose target case lecturer's rapid movement. This article proposes based on MobileNet-SSD face detection Pedestrian Dead Reckoning (PDR) technology solve this problem. First, particle filter algorithm used fuse PDR information with rotation angle...

Previously a novel chaotic transmission method was proposed in air traffic voice communication system, which applied remote radio control transmission. It has better performance than Frequency Shift Keying efficiency, bandwidth and anti-additive-white-noise performance. However, the channel noise great effect on method. Thus problem of modulated signals affected by how to design M-ary system additive color Gauss for data are studied this paper. Firstly, signals' boundary range white is...

To binocular camera, the consistency of optical parameters left and right system is an important factor that will influence overall imaging consistency. In conventional testing procedure system, there lacks specifications suitable for evaluating this paper, considering special requirements a method used to measure camera presented. Based on method, measurement which composed integrating sphere, rotary table CMOS has been established. First, let capture images in normal exposure time under...

Audio-visual segmentation (AVS) is a challenging task that involves accurately segmenting sounding objects based on audio-visual cues. The effectiveness of learning critically depends achieving accurate cross-modal alignment between sound and visual objects. Successful requires two essential components: 1) dataset with high-quality pixel-level multi-class annotated images associated audio files, 2) model can establish strong links information its corresponding object. However, these...

Abstract Current deep image super-resolution (SR) approaches aim to restore high-resolution images from down-sampled or by assuming degradation simple Gaussian kernels and additive noises. However, these techniques only assume crude approximations of the real-world process, which should involve complex noise patterns that are difficult model using assumptions. In this paper, we propose a more realistic process synthesise low-resolution for SR introducing new Kernel Adversarial Learning...

The missing modality issue is critical but non-trivial to be solved by multi-modal models. Current methods aiming handle the problem in tasks, either deal with modalities only during evaluation or train separate models specific settings. In addition, these are designed for so example, classification not easily adapted segmentation tasks and vice versa. this paper, we propose Shared-Specific Feature Modelling (ShaSpec) method that considerably simpler more effective than competing approaches...

Considering the conditional constraints in urban environment, traditional method of detecting drones is not applicable, and combining target detection with it an effective solution. We propose a lightweight object model based on YOLOv7. The replaces Backbone network MobileViTv3, which reduces number parameters model; Secondly, SPD-Conv module introduced to increase accuracy small-sized drones; In addition, we integrate SimAM Module (Simple, Parameter-Free Attention Module) find important...

The problem of missing modalities is both critical and non-trivial to be handled in multi-modal models. It common for tasks that certain contribute more compared other modalities, if those important are missing, the model performance drops significantly. Such fact remains unexplored by current approaches recover representation from feature reconstruction or blind aggregation instead extracting useful information best performing modalities. In this paper, we propose a Learnable Cross-modal...

The new generation of organic light emitting diode display is designed to enable the high dynamic range (HDR), going beyond standard (SDR) supported by traditional devices. However, a large quantity videos are still SDR format. Further, most pre-existing compressed at varying degrees for minimizing storage and traffic flow demands. To movie-going experience on devices, converting HDR format (i.e., <italic xmlns:mml="http://www.w3.org/1998/Math/MathML"...

We design a system for risk-analyzing and pricing portfolios of non-performing consumer credit loans. The rapid development lending business consumers heightens the need trading formed by overdue loans as manner risk transferring. However, problem is nontrivial technically related research absent. tackle challenge building bottom-up architecture, in which we model distribution every single loan's repayment rate, followed modeling portfolio's overall rate. To address technical issues...

Current deep image super-resolution (SR) approaches attempt to restore high-resolution images from down-sampled or by assuming degradation simple Gaussian kernels and additive noises. However, such processing techniques represent crude approximations of the real-world procedure lowering resolution. In this paper, we propose a more realistic process lower resolution introducing new Kernel Adversarial Learning Super-resolution (KASR) framework deal with SR problem. proposed framework, noises...