Dgrnet: A dual-level graph relation network for video object detection
Video object detection is a fundamental and important task in computer vision. One mainstay
solution for this task is to aggregate features from different frames to enhance the detection …
solution for this task is to aggregate features from different frames to enhance the detection …
Class-aware dual-supervised aggregation network for video object detection
Video object detection has attracted increasing attention in recent years. Although great
success has been achieved by off-the-shelf video object detection methods through …
success has been achieved by off-the-shelf video object detection methods through …
IMC-Det: Intra–Inter Modality Contrastive Learning for Video Object Detection
Video object detection is an important yet challenging task in the computer vision field. One
limitation of off-the-shelf video object detection methods is that they only explore information …
limitation of off-the-shelf video object detection methods is that they only explore information …
Kinematics-aware spatial-temporal feature transform for 3D human pose estimation
S Du, Z Yuan, T Ikenaga - Pattern Recognition, 2024 - Elsevier
Abstract 3D human pose estimation plays an important role in various human-machine
interactive applications, but how to effectively extract and represent the kinematical features …
interactive applications, but how to effectively extract and represent the kinematical features …
Future Feature-Based Supervised Contrastive Learning for Streaming Perception
T Wang, H Huang - IEEE Transactions on Circuits and Systems …, 2024 - ieeexplore.ieee.org
Streaming perception, a critical task in computer vision, involves the real-time prediction of
object locations within video sequences based on prior frames. While current methods like …
object locations within video sequences based on prior frames. While current methods like …
TCNet: A novel triple-cooperative network for video object detection
Video object detection aims at accurately localizing the objects in videos and correctly
recognizing their categories. Off-the-shelf video object detection methods have made some …
recognizing their categories. Off-the-shelf video object detection methods have made some …
Temporal early exits for efficient video object detection
Transferring image-based object detectors to the domain of video remains challenging
under resource constraints. Previous efforts utilised optical flow to allow unchanged features …
under resource constraints. Previous efforts utilised optical flow to allow unchanged features …
Context-aware and Semantic-consistent Spatial Interactions for One-shot Object Detection without Fine-tuning
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 …
attention and research focus. It aims to directly detect novel-class objects in the target image …
Weakly Supervised Fixated Object Detection in Traffic Videos based on Driver's Selective Attention Mechanism
Y Shi, L Qin, S Zhao, K Yang, Y Cui… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Traffic scene perception has a significant impact on driving safety. Inexperienced or
distracted drivers usually do not allocate enough attention to the objects closely related to …
distracted drivers usually do not allocate enough attention to the objects closely related to …
Joint Spatial and Temporal Feature Enhancement Network for Disturbed Object Detection
Video object detection remains a challenging task due to appearance degradation in certain
frames. Existing studies usually aggregate temporal information from multiple frames to …
frames. Existing studies usually aggregate temporal information from multiple frames to …