Papers Motion Compensation
“Motion Compensation” 태그가 달린 논문 207편 · 필터 해제
SAM4D: Segment Anything in Camera and LiDAR Streams
We present SAM4D, a multi-modal and temporal foundation model designed for promptable segmentation across camera and LiDAR streams. Unified Multi-modal Positional Encoding (UMPE) is introduced to align camera and LiDAR f…
4D reconstructionAutonomous DrivingMotion CompensationSegmentationDualX-VSR: Dual Axial Spatial$\times$Temporal Transformer for Real-World Video Super-Resolution without Motion Compensation
Transformer-based models like ViViT and TimeSformer have advanced video understanding by effectively modeling spatiotemporal dependencies. Recent video generation models, such as Sora and Vidu, further highlight the powe…
Motion CompensationOptical Flow EstimationSuper-ResolutionVideo Generation+2AceVFI: A Comprehensive Survey of Advances in Video Frame Interpolation
Video Frame Interpolation (VFI) is a fundamental Low-Level Vision (LLV) task that synthesizes intermediate frames between existing ones while maintaining spatial and temporal coherence. VFI techniques have evolved from c…
MambaMotion CompensationSurveyVideo Frame InterpolationNonlinear Motion-Guided and Spatio-Temporal Aware Network for Unsupervised Event-Based Optical Flow
Event cameras have the potential to capture continuous motion information over time and space, making them well-suited for optical flow estimation. However, most existing learning-based methods for event-based optical fl…
Event-based Optical FlowMotion CompensationOptical Flow EstimationImproving trajectory continuity in drone-based crowd monitoring using a set of minimal-cost techniques and deep discriminative correlation filters
Drone-based crowd monitoring is the key technology for applications in surveillance, public safety, and event management. However, maintaining tracking continuity and consistency remains a significant challenge. Traditio…
Computational EfficiencyMotion CompensationObject TrackingImproved Motion Plane Adaptive 360-Degree Video Compression Using Affine Motion Models
Efficient compression of 360-degree video content requires the application of advanced motion models for interframe prediction. The Motion Plane Adaptive (MPA) motion model projects the frames on multiple perspective pla…
Motion CompensationMotion EstimationVideo CompressionResidual Learning and Filtering Networks for End-to-End Lossless Video Compression
Existing learning-based video compression methods still face challenges related to inaccurate motion estimates and inadequate motion compensation structures. These issues result in compression errors and a suboptimal rat…
Motion CompensationMotion EstimationVideo CompressionHiMo: High-Speed Objects Motion Compensation in Point Clouds
LiDAR point cloud is essential for autonomous vehicles, but motion distortions from dynamic objects degrade the data quality. While previous work has considered distortions caused by ego motion, distortions caused by oth…
Autonomous VehiclesMotion CompensationScene Flow EstimationSemantic SegmentationAn Experimental Study of SOTA LiDAR Segmentation Models
Point cloud segmentation (PCS) is to classify each point in point clouds. The task enables robots to parse their 3D surroundings and run autonomously. According to different point cloud representations, existing PCS mode…
GPUMotion CompensationPoint Cloud SegmentationPD-SORT: Occlusion-Robust Multi-Object Tracking Using Pseudo-Depth Cues
Multi-object tracking (MOT) is a rising topic in video processing technologies and has important application value in consumer electronics. Currently, tracking-by-detection (TBD) is the dominant paradigm for MOT, which p…
Motion CompensationMulti-Object TrackingObject TrackingFLAVC: Learned Video Compression with Feature Level Attention
Learned Video Compression (LVC) aims to reduce redundancy in sequential data through deep learning approaches. Recent advances have significantly boosted LVC performance by shifting compression operations to feature …
Motion CompensationMotion EstimationVideo CompressionLearning Monocular Depth from Events via Egomotion Compensation
Event cameras are neuromorphically inspired sensors that sparsely and asynchronously report brightness changes. Their unique characteristics of high temporal resolution, high dynamic range, and low power consumption make…
Depth EstimationMonocular Depth EstimationMotion CompensationHybrid Local-Global Context Learning for Neural Video Compression
In neural video codecs, current state-of-the-art methods typically adopt multi-scale motion compensation to handle diverse motions. These methods estimate and compress either optical flow or deformable offsets to reduce …
Motion CompensationMotion EstimationOptical Flow EstimationVideo CompressionMotion Free B-frame Coding for Neural Video Compression
Typical deep neural video compression networks usually follow the hybrid approach of classical video coding that contains two separate modules: motion coding and residual coding. In addition, a symmetric auto-encoder is …
Motion CompensationMotion EstimationVideo CompressionU-Motion: Learned Point Cloud Video Compression with U-Structured Temporal Context Generation
Point cloud video (PCV) is a versatile 3D representation of dynamic scenes with emerging applications. This paper introduces U-Motion, a learning-based compression scheme for both PCV geometry and attributes. We propose …
AttributeMotion CompensationMotion EstimationVideo CompressionEfficient single image non-uniformity correction algorithm
This paper introduces a new way to correct the non-uniformity (NU) in uncooled infrared-type images. The main defect of these uncooled images is the lack of a column (resp. line) time-dependent cross-calibration, resulti…
Motion CompensationUnsupervised Training of a Dynamic Context-Aware Deep Denoising Framework for Low-Dose Fluoroscopic Imaging
Fluoroscopy is critical for real-time X-ray visualization in medical imaging. However, low-dose images are compromised by noise, potentially affecting diagnostic accuracy. Noise reduction is crucial for maintaining image…
DenoisingDiagnosticKnowledge DistillationMotion CompensationVETRA: A Dataset for Vehicle Tracking in Aerial Imagery - New Challenges for Multi-Object Tracking
The informative power of traffic analysis can be enhanced by considering changes in both time and space. Vehicle tracking algorithms applied to drone videos provide a better overview than street-level surveillance camera…
de-enMotion CompensationMulti-Object TrackingObject TrackingInfrared Small Target Detection in Satellite Videos: A New Dataset and A Novel Recurrent Feature Refinement Framework
Multi-frame infrared small target (MIRST) detection in satellite videos is a long-standing, fundamental yet challenging task for decades, and the challenges can be summarized as: First, extremely small target size, highl…
Motion CompensationVideo GenerationOne Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation
A novel online MOT algorithm, IMM Joint Homography State Estimation (IMM-JHSE), is proposed. IMM-JHSE uses an initial homography estimate as the only additional 3D information, whereas other 3D MOT methods use regular 3D…
AllMotion CompensationMulti-Object Tracking+3