Papers Video Panoptic Segmentation
“Video Panoptic Segmentation” 태그가 달린 논문 44편 · 필터 해제
Scene-Centric Unsupervised Video Panoptic Segmentation
Video panoptic segmentation (VPS) aims to jointly detect, segment, and track all objects while partitioning the video into semantically consistent regions. We introduce the task setting of unsupervised VPS, omitting any …
Video Panoptic SegmentationScene UnderstandingVideo SegmentationImage SegmentationSPORTS: Simultaneous Panoptic Odometry, Rendering, Tracking and Segmentation for Urban Scenes Understanding
The scene perception, understanding, and simulation are fundamental techniques for embodied-AI agents, while existing solutions are still prone to segmentation deficiency, dynamic objects' interference, sensor data spars…
Video Panoptic SegmentationCamera Pose EstimationNovel View SynthesisScene UnderstandingA Comprehensive Survey on Video Scene Parsing:Advances, Challenges, and Prospects
Video Scene Parsing (VSP) has emerged as a cornerstone in computer vision, facilitating the simultaneous segmentation, recognition, and tracking of diverse visual entities in dynamic scenes. In this survey, we present a …
BenchmarkingInstance SegmentationOpen-Vocabulary Video SegmentationPanoptic Segmentation+8MM-OR: A Large Multimodal Operating Room Dataset for Semantic Understanding of High-Intensity Surgical Environments
Operating rooms (ORs) are complex, high-stakes environments requiring precise understanding of interactions among medical staff, tools, and equipment for enhancing surgical assistance, situational awareness, and patient …
2D Panoptic SegmentationGraph GenerationLanguage ModelingLanguage Modelling+2LiDAR-Camera Fusion for Video Panoptic Segmentation without Video Training
Panoptic segmentation, which combines instance and semantic segmentation, has gained a lot of attention in autonomous vehicles, due to its comprehensive representation of the scene. This task can be applied for cameras a…
Autonomous VehiclesPanoptic SegmentationSegmentationSemantic Segmentation+1Balancing Shared and Task-Specific Representations: A Hybrid Approach to Depth-Aware Video Panoptic Segmentation
In this work, we present Multiformer, a novel approach to depth-aware video panoptic segmentation (DVPS) based on the mask transformer paradigm. Our method learns object representations that are shared across segmentatio…
DecoderDepth-aware Video Panoptic SegmentationDepth EstimationMonocular Depth Estimation+4MGNiceNet: Unified Monocular Geometric Scene Understanding
Monocular geometric scene understanding combines panoptic segmentation and self-supervised depth estimation, focusing on real-time application in autonomous vehicles. We introduce MGNiceNet, a unified approach that uses …
Autonomous DrivingAutonomous VehiclesDepth EstimationDepth Prediction+5Configurable Embodied Data Generation for Class-Agnostic RGB-D Video Segmentation
This paper presents a method for generating large-scale datasets to improve class-agnostic video segmentation across robots with different form factors. Specifically, we consider the question of whether video segmentatio…
BenchmarkingPanoptic SegmentationSegmentationVideo Panoptic Segmentation+2Context-Aware Video Instance Segmentation
In this paper, we introduce the Context-Aware Video Instance Segmentation (CAVIS), a novel framework designed to enhance instance association by integrating contextual information adjacent to each object. To efficiently …
Instance SegmentationPanoptic SegmentationSegmentationSemantic Segmentation+2Uni-DVPS: Unified Model for Depth-Aware Video Panoptic Segmentation
We present Uni-DVPS, a unified model for Depth-aware Video Panoptic Segmentation (DVPS) that jointly tackles distinct vision tasks, i.e., video panoptic segmentation, monocular depth estimation, and object tracking. In c…
Autonomous DrivingDecoderDepth-aware Video Panoptic SegmentationDepth Estimation+71st Place Winner of the 2024 Pixel-level Video Understanding in the Wild (CVPR'24 PVUW) Challenge in Video Panoptic Segmentation and Best Long Video Consistency of Video Semantic Segmentation
The third Pixel-level Video Understanding in the Wild (PVUW CVPR 2024) challenge aims to advance the state of art in video understanding through benchmarking Video Panoptic Segmentation (VPS) and Video Semantic Segmentat…
BenchmarkingInstance SegmentationPanoptic SegmentationScene Parsing+63rd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation
Video panoptic segmentation is an advanced task that extends panoptic segmentation by applying its concept to video sequences. In the hope of addressing the challenge of video panoptic segmentation in diverse conditions,…
Panoptic SegmentationSegmentationVideo Panoptic SegmentationVideo Understanding2nd Place Solution for PVUW Challenge 2024: Video Panoptic Segmentation
Video Panoptic Segmentation (VPS) is a challenging task that is extends from image panoptic segmentation.VPS aims to simultaneously classify, track, segment all objects in a video, including both things and stuff. Due to…
Autonomous DrivingPanoptic SegmentationSegmentationSemantic Segmentation+3An Integrated Framework for Multi-Granular Explanation of Video Summarization
In this paper, we propose an integrated framework for multi-granular explanation of video summarization. This framework integrates methods for producing explanations both at the fragment level (indicating which video fra…
BenchmarkingPanoptic SegmentationVideo Panoptic SegmentationVideo SummarizationUniVS: Unified and Universal Video Segmentation with Prompts as Queries
Despite the recent advances in unified image segmentation (IS), developing a unified video segmentation (VS) model remains a challenge. This is mainly because generic category-specified VS tasks need to detect all object…
DecoderReferring Expression SegmentationReferring Video Object SegmentationVideo Instance Segmentation+6DVIS++: Improved Decoupled Framework for Universal Video Segmentation
We present the \textbf{D}ecoupled \textbf{VI}deo \textbf{S}egmentation (DVIS) framework, a novel approach for the challenging task of universal video segmentation, including video instance segmentation (VIS), video seman…
Contrastive LearningDenoisingInstance SegmentationPanoptic Segmentation+6A Simple Video Segmenter by Tracking Objects Along Axial Trajectories
Video segmentation requires consistently segmenting and tracking objects over time. Due to the quadratic dependency on input size, directly applying self-attention to video segmentation with high-resolution input feature…
GPUObjectObject TrackingPanoptic Segmentation+5SANPO: A Scene Understanding, Accessibility and Human Navigation Dataset
Vision is essential for human navigation. The World Health Organization (WHO) estimates that 43.3 million people were blind in 2020, and this number is projected to reach 61 million by 2050. Modern scene understanding mo…
Autonomous VehiclesDepth EstimationDomain AdaptationPanoptic Segmentation+5PAg-NeRF: Towards fast and efficient end-to-end panoptic 3D representations for agricultural robotics
Precise scene understanding is key for most robot monitoring and intervention tasks in agriculture. In this work we present PAg-NeRF which is a novel NeRF-based system that enables 3D panoptic scene understanding. Our re…
3D ReconstructionCamera LocalizationNeRFPanoptic Segmentation+3Tracking Anything with Decoupled Video Segmentation
Training data for video segmentation are expensive to annotate. This impedes extensions of end-to-end algorithms to new video segmentation tasks, especially in large-vocabulary settings. To 'track anything' without train…
Open-Vocabulary Video SegmentationOpen-World Video SegmentationPanoptic SegmentationReferring Expression Segmentation+9