IEEE Transactions on Circuits and Systems for Video Technology

This paper develops an extremely robust solution for absolute pose estimation with known prior gravity direction by motion decoupling. Absolute pose estimation is a fundamental problem in computer vision, and recently the prior known vertical direction is ...

Automatic tooth instance segmentation on 3D dental models is crucial for digitizing dental treatments and enabling computer-assisted treatment planning. However, It is challenging since the tight arrangement of dental structures and the consequential ...

Online cross-modal hashing has received increasing research attention due to its capability of encoding streaming data and updating hash functions simultaneously. Despite significant progress, there is still room for further improving accuracy from two ...

Deep learning based object detection methods have made significant progress in recent years. However, these methods often suffer from a substantial performance drop when domain shifts occur, making it difficult to generalize a source domain trained object ...

Image captioning (IC) takes an image as input and generates open-form descriptions in the domain of natural language. IC requires the detection of objects, modeling of relations between them, an assessment of the semantics of the scene and representing ...

Compared with natural image segmentation, small sample image segmentation tasks, such as medical image segmentation and defect detection, have been less studied. Recent studies made efforts on bringing together Convolutional Neural Networks (CNNs) and ...

The current mainstream studies on Scene Graph Generation (SGG) devote to the long-tailed predicate distribution problem to generate unbiased scene graph. The long-tailed predicate distribution exists in VG dataset and is more severe during the SGG network ...

Despite deep neural networks have made outstanding achievements in many static tasks, when faced with a continuous stream of data, they suffer from catastrophic forgetting since the previous data is usually inaccessible. Stored data or generative model is ...

Recent advanced trackers, composed of discriminative classification and dedicated bounding box estimation, have achieved remarkable advancements in performance of visual object tracking. However, existing methods cannot satisfy the demands of tracking ...

Replacing objects in images is a practical functionality of Photoshop, e.g., clothes changing. This task is defined as Unsupervised Deformable-Instances Image-to-Image Translation (UDIT), which maps multiple foreground instances of a source domain to a ...

Feature pyramid representations have been widely adopted in the object detection literature for better handling of variations in scale, which provide abundant information from various spatial levels for classification and localization sub-tasks. We find ...

Reducing cumulative registration error is critical to accurate 3D multi-view registration. Meta-shape based methods optimize rigid transformations of point clouds by iteratively registering each point cloud with a meta-shape, which remain popular ...

Despite recent progress, Video Object Segmentation (VOS) remains challenging in complex situations such as low light and dark scenes. In this paper, we tackle the visibility limitations by introducing thermal information as auxillary for VOS. Specifically,...

Superpixel segmentation divides an original image into mid-level regions to reduce the number of computational primitives for subsequent tasks. The two-stage approaches work better but have high computational complexity among the existing deep superpixel ...

We propose a novel Text-to-Image Generation Network, Attention-bridged Modal Interaction Generative Adversarial Network (AMI-GAN), to better explore modal interaction and perception for high-quality image synthesis. The AMI-GAN contains two novel designs: ...

Due to the various appearance of the polyps and the tiny contrast between the polyp area and its surrounding background, accurate polyp segmentation has become a challenging task. To tackle this issue, we introduce a boundary-enhanced framework for polyp ...

One-shot object detection (OSOD) without fine-tuning has recently garnered considerable attention and research focus. It aims to directly detect novel-class objects in the target image by providing merely one support image patch without undergoing the ...

Micro-video venue recognition aims to predict the venue category where a micro-video was filmed. Different from traditional long videos which contain rich temporal context, venue prediction for micro-videos is difficult due to its limited duration (...

Camouflaged Object Detection (COD) is a challenging visual task due to its complex contour, diverse scales, and high similarity to the background. Existing COD methods encounter two predicaments: One is that they are prone to falling into local perception,...

Face swapping aims to transfer the identity of a source face to a target face image while preserving the target attributes (e.g., facial expression, head pose, illumination, and background). Most existing methods use a face recognition model to extract ...

With a focus on abnormal events contained within untrimmed videos, there is increasing interest among researchers in video anomaly detection. Among different video anomaly detection scenarios, weakly-supervised video anomaly detection poses a significant ...

FSCIL (Few-shot class-incremental learning) is a prominent research topic in the ML community. It faces two significant challenges: forgetting old class knowledge and overfitting to limited new class training examples. In this paper, we present a novel ...

In this paper, we investigate the dynamics-aware adversarial attack problem of adaptive neural networks. Most existing adversarial attack algorithms are designed under a basic assumption – the network architecture is fixed throughout the attack ...

Benefiting from the rich information provided by different modalities, multi-modal tracking has shown significant improvements compared to single-modal tracking. However, in practical applications, multi-modal tracking still faces two major challenges. ...

Nuclear norm maximization has shown the power to enhance the transferability of unsupervised domain adaptation model (UDA) in an empirical scheme. In this paper, we identify a new property termed equity, which indicates the balance degree of predicted ...

Image-to-image (I2I) translation often requires establishing cycle consistency between the source and the translated images across different domains. However, cycle consistency requires redundant reconstruction, and is too restrictive to satisfy the ...

Few-shot semantic segmentation (FSS) aims to segment novel classes with only a few annotated samples. Existing methods to FSS generally combine the annotated mask and the corresponding support image to generate the class-specific representation, and ...

Action learning is a research area that aims to recognize the action category of each frame in the video. Context information is crucial for learning actions, but most existing methods face two challenges in exploiting this information: 1) They apply ...

Recent development in computing power has resulted in performance improvements on holistic (none-occluded) person Re-Identification (ReID) tasks. Nevertheless, the precision of the recent research will diminish when a pedestrian is obstructed by ...

Human-Object Interaction (HOI) detection is a fertile research ground that merits further investigation in computer vision, and plays an important role in image high-level semantic information understanding. To achieve superior object detection ...