Papers Semi-Supervised Video Object Segmentation
“Semi-Supervised Video Object Segmentation” 태그가 달린 논문 154편 · 필터 해제
Global Spectral Filter Memory Network for Video Object Segmentation
This paper studies semi-supervised video object segmentation through boosting intra-frame interaction. Recent memory network-based methods focus on exploiting inter-frame temporal reference while paying little attention …
AttributeDecoderObjectSegmentation+4Pixel-Level Equalized Matching for Video Object Segmentation
Feature similarity matching, which transfers the information of the reference frame to the query frame, is a key component in semi-supervised video object segmentation. If surjective matching is adopted, background distr…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1SWEM: Towards Real-Time Video Object Segmentation with Sequential Weighted Expectation-Maximization
Matching-based methods, especially those based on space-time memory, are significantly ahead of other solutions in semi-supervised video object segmentation (VOS). However, continuously growing and redundant template fea…
Semantic SegmentationSemi-Supervised Video Object SegmentationVideo Object SegmentationVideo Semantic SegmentationPer-Clip Video Object Segmentation
Recently, memory-based approaches show promising results on semi-supervised video object segmentation. These methods predict object masks frame-by-frame with the help of frequently updated memory of the previous mask. Di…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2BATMAN: Bilateral Attention Transformer in Motion-Appearance Neighboring Space for Video Object Segmentation
Video Object Segmentation (VOS) is fundamental to video understanding. Transformer-based methods show significant performance improvement on semi-supervised VOS. However, existing work faces challenges segmenting visuall…
ObjectOptical Flow EstimationSegmentationSemantic Segmentation+5Region Aware Video Object Segmentation with Deep Motion Modeling
Current semi-supervised video object segmentation (VOS) methods usually leverage the entire features of one frame to predict object masks and update memory. This introduces significant redundant computations. To reduce r…
DecoderObjectSegmentationSemantic Segmentation+3Learning Quality-aware Dynamic Memory for Video Object Segmentation
Recently, several spatial-temporal memory-based methods have verified that storing intermediate frames and their masks as memory are helpful to segment target objects in videos. However, they mainly focus on better match…
SegmentationSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1XMem: Long-Term Video Object Segmentation with an Atkinson-Shiffrin Memory Model
We present XMem, a video object segmentation architecture for long videos with unified feature memory stores inspired by the Atkinson-Shiffrin memory model. Prior work on video object segmentation typically only uses one…
2D Human Pose Estimation2D Object Detection3D Absolute Human Pose EstimationSegmentation+4Tackling Background Distraction in Video Object Segmentation
Semi-supervised video object segmentation (VOS) aims to densely track certain designated objects in videos. One of the main challenges in this task is the existence of background distractors that appear similar to the ta…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Towards Robust Video Object Segmentation with Adaptive Object Calibration
In the booming video era, video segmentation attracts increasing research attention in the multimedia community. Semi-supervised video object segmentation (VOS) aims at segmenting objects in all target frames of a video,…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+4The Second Place Solution for The 4th Large-scale Video Object Segmentation Challenge--Track 3: Referring Video Object Segmentation
The referring video object segmentation task (RVOS) aims to segment object instances in a given video referred by a language expression in all video frames. Due to the requirement of understanding cross-modal semantics w…
Objectobject-detectionObject DetectionReferring Video Object Segmentation+5Collaborative Attention Memory Network for Video Object Segmentation
Semi-supervised video object segmentation is a fundamental yet Challenging task in computer vision. Embedding matching based CFBI series networks have achieved promising results by foreground-background integration appro…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2Recurrent Dynamic Embedding for Video Object Segmentation
Space-time memory (STM) based video object segmentation (VOS) networks usually keep increasing memory bank every several frames, which shows excellent performance. However, 1) the hardware cannot withstand the ever-incre…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Boosting Video Object Segmentation based on Scale Inconsistency
We present a refinement framework to boost the performance of pre-trained semi-supervised video object segmentation (VOS) models. Our work is based on scale inconsistency, which is motivated by the observation that exist…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1Adaptive Memory Management for Video Object Segmentation
Matching-based networks have achieved state-of-the-art performance for video object segmentation (VOS) tasks by storing every-k frames in an external memory bank for future inference. Storing the intermediate frames' pre…
ManagementObjectSegmentationSemantic Segmentation+3Scalable Video Object Segmentation with Identification Mechanism
This paper delves into the challenges of achieving scalable and effective multi-object modeling for semi-supervised Video Object Segmentation (VOS). Previous VOS methods decode features with a single positive object, lim…
ObjectSegmentationSemantic SegmentationSemi-Supervised Video Object Segmentation+2MixFormer: End-to-End Tracking with Iterative Mixed Attention
Tracking often uses a multi-stage pipeline of feature extraction, target information integration, and bounding box estimation. To simplify this pipeline and unify the process of feature extraction and target information …
Semi-Supervised Video Object SegmentationVideo Object TrackingVisual Object TrackingSiamese Network with Interactive Transformer for Video Object Segmentation
Semi-supervised video object segmentation (VOS) refers to segmenting the target object in remaining frames given its annotation in the first frame, which has been actively studied in recent years. The key challenge lies …
DecoderObjectSemantic SegmentationSemi-Supervised Video Object Segmentation+2Reliable Propagation-Correction Modulation for Video Object Segmentation
Error propagation is a general but crucial problem in online semi-supervised video object segmentation. We aim to suppress error propagation through a correction mechanism with high reliability. The key insight is to dis…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1MUNet: Motion Uncertainty-aware Semi-supervised Video Object Segmentation
The task of semi-supervised video object segmentation (VOS) has been greatly advanced and state-of-the-art performance has been made by dense matching-based methods. The recent methods leverage space-time memory (STM) ne…
ObjectSemantic SegmentationSemi-Supervised Video Object SegmentationVideo Object Segmentation+1