This competition is dedicated to achieving fisheye object detection in Asia, particularly in countries like Taiwan, while emphasizing low power consumption and simultaneously achieving a high mean average precision (mAP). This task is notably challenging ...

During the competition, several factors that could decrease the effectiveness of the training result was quickly identified, such as the lack of distortion of provided training data, the high similarity between multiple images, and the extreme imbalance ...

In this paper, we introduce a lightweight object detection system, custom-designed for fisheye cameras and optimized for quick deployment on embedded systems. Given the constraints of training solely on standard images, our methodology centers on the ...

The Panoptic Scene Graph generation (PSG) task aims to extract the triplets composed of subject, object, and relation based on panoptic segmentation. For one-stage methods, PSGTR predicts the subject, object, and relation by one query. However, the ...

Currently, the results of makeup transfer are generally satisfactory in most scenarios. However, the transfer results show that the transfer makeup details is not accurate, such as in blush and lip corners. To this end, we propose a variant model of ...

Group formation is fundamental for 3D displays that use Flying Light Specks, FLSs, to illuminate shapes and provide haptic interactions. An FLS is a drone with light sources that illuminates a shape. Groups of G FLSs may implement reliability techniques ...

In this paper, a novel pose estimation algorithm is proposed specifically for maneuvering airplanes in the air. The algorithm consists of two main stages. The first stage involves semantic segmentation of a monocular input image of a flying airplane, ...

Zero-Shot Action Recognition (ZSAR) enables models to infer new action classes from previously seen data without any samples of those new classes. How an action class is represented in an understandable and processable format influences the performance ...

Nutrition plays a vital role in overall health and well-being. With a highly accurate nutrient estimation model, we develop a tool that displays nutritional values from food images, thereby reducing the labor-intensiveness of dietary assessment. We ...

3D point cloud semantic segmentation is a fundamental task for 3D scene understanding. However, most existing pipelines usually use k-NN or ball query operation to form hard neighborhoods, which may cross different semantic objects, resulting low-...

Indoor understanding is currently a topic that is widely studied in the field of machine learning. Furniture is the most common object in indoor scenes, just as various vehicles are most commonly seen in street scenes. Any object is made up of a ...

Recently, Transformer based visual object tracking methods have achieved impressive advancements and significantly improved tracking performance. Transformer includes two modules of self-attention and cross-attention for those methods. However, it ...

Matching-based methods have becamed popular in semi-supervised video object segmentation (VOS), by maintaining a memory bank to predict object masks. However, these methods encounter challenges for fast motions and appearance changes, resulting in ...

Recently, neural network-based image compression techniques have demonstrated remarkable compression performance. The use of context-adaptive entropy models greatly enhances the rate-distortion (R-D) performance by effectively capturing spatial ...

Nighttime image dehazing is critical for many computer applications. Directly transferring daytime dehazing models to nighttime scenes often introduces haze residual, detail loss and color distortion for the uneven distribution by artificial lights. ...

RGB-Thermal salient object detection (RGB-T SOD) aims to locate salient objects in images that include both RGB and thermal information. Previous approaches often suggest designing a symmetric network structure to tackle the challenge of dealing with ...

In recent years, there have been a growing interest in developing end-to-end neural video codecs. Previous works generally use a past decoded frame as reference directly, utilizing the motion information between it and the input frame to reduce temporal ...

Geometric style transfer jointly stylizes the texture and geometry of a content image to better match a style image, which has attracted widespread attention due to its various applications. However, existing style transfer methods either primarily ...

Attention-based Transformer models have achieved remarkable progress in multi-modal tasks, such as visual question answering. The explainability of attention-based methods has recently attracted wide interest as it can explain the inner changes of ...

Parking slot detection is an essential yet challenging task in the field of self-driving perception. During parking, vehicles often block part of the parking slots which makes the corners occluded. In addition, due to the impact of the external ...