Papers Video Object Tracking
“Video Object Tracking” 태그가 달린 논문 107편 · 필터 해제
Revealing the Dark Secrets of Masked Image Modeling
Masked image modeling (MIM) as pre-training is shown to be effective for numerous vision downstream tasks, but how and where MIM works remain unclear. In this paper, we compare MIM with the long-dominant supervised pre-t…
Depth EstimationDiversityInductive BiasMonocular Depth Estimation+4Learning What and Where: Disentangling Location and Identity Tracking Without Supervision
Our brain can almost effortlessly decompose visual data streams into background and salient objects. Moreover, it can anticipate object motion and interactions, which are crucial abilities for conceptual planning and rea…
ObjectVideo Object TrackingVideo Polyp Segmentation: A Deep Learning Perspective
We present the first comprehensive video polyp segmentation (VPS) study in the deep learning era. Over the years, developments in VPS are not moving forward with ease due to the lack of large-scale fine-grained segmentat…
AttributeDeep LearningSegmentationSemantic Segmentation+3Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
The current popular two-stream, two-stage tracking framework extracts the template and the search region features separately and then performs relation modeling, thus the extracted features lack the awareness of the targ…
Object TrackingRelationVideo Object TrackingVisual Object Tracking+1MixFormer: 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 TrackingTransforming Model Prediction for Tracking
Optimization based tracking methods have been widely successful by integrating a target model prediction module, providing effective global reasoning by minimizing an objective function. While this inductive bias integra…
Inductive BiasmodelPredictionVideo Object Tracking+1Robust Visual Tracking by Segmentation
Estimating the target extent poses a fundamental challenge in visual object tracking. Typically, trackers are box-centric and fully rely on a bounding box to define the target in the scene. In practice, objects often hav…
DecoderObject TrackingSegmentationSemantic Segmentation+5TFCNet: Temporal Fully Connected Networks for Static Unbiased Temporal Reasoning
Temporal Reasoning is one important functionality for vision intelligence. In computer vision research community, temporal reasoning is usually studied in the form of video classification, for which many state-of-the-art…
Action RecognitionClassificationVideo ClassificationVideo Object TrackingEfficient Visual Tracking with Exemplar Transformers
The design of more complex and powerful neural network models has significantly advanced the state-of-the-art in visual object tracking. These advances can be attributed to deeper networks, or the introduction of new bui…
CPUObject TrackingVideo Object TrackingVisual Object Tracking+1Evaluating and Improving Interactions with Hazy Oracles
Many AI systems integrate sensor inputs, world knowledge, and human-provided information to perform inference. While such systems often treat the human input as flawless, humans are better thought of as hazy oracles whos…
Object TrackingReferring ExpressionReferring Expression ComprehensionVideo Object Tracking+3INFERNO: Inferring Object-Centric 3D Scene Representations without Supervision
We propose INFERNO, a method to infer object-centric representations of visual scenes without relying on annotations. Our method learns to decompose a scene into multiple objects, each object having a structured represen…
ObjectVideo Object TrackingVisual ReasoningBundleTrack: 6D Pose Tracking for Novel Objects without Instance or Category-Level 3D Models
Tracking the 6D pose of objects in video sequences is important for robot manipulation. Most prior efforts, however, often assume that the target object's CAD model, at least at a category-level, is available for offline…
3D Object Tracking6D Pose Estimation6D Pose Estimation using RGB6D Pose Estimation using RGBD+7Do Different Tracking Tasks Require Different Appearance Models?
Tracking objects of interest in a video is one of the most popular and widely applicable problems in computer vision. However, with the years, a Cambrian explosion of use cases and benchmarks has fragmented the problem i…
Multi-Object TrackingMulti-Object Tracking and SegmentationMultiple People TrackingObject Tracking+10ADTrack: Target-Aware Dual Filter Learning for Real-Time Anti-Dark UAV Tracking
Prior correlation filter (CF)-based tracking methods for unmanned aerial vehicles (UAVs) have virtually focused on tracking in the daytime. However, when the night falls, the trackers will encounter more harsh scenes, wh…
CPUVideo Object TrackingLightTrack: Finding Lightweight Neural Networks for Object Tracking via One-Shot Architecture Search
Object tracking has achieved significant progress over the past few years. However, state-of-the-art trackers become increasingly heavy and expensive, which limits their deployments in resource-constrained applications. …
GPUNeural Architecture SearchObjectObject Tracking+1STMTrack: Template-free Visual Tracking with Space-time Memory Networks
Boosting performance of the offline trained siamese trackers is getting harder nowadays since the fixed information of the template cropped from the first frame has been almost thoroughly mined, but they are poorly capab…
Video Object TrackingVisual Object TrackingVisual TrackingLearning Spatio-Temporal Transformer for Visual Tracking
In this paper, we present a new tracking architecture with an encoder-decoder transformer as the key component. The encoder models the global spatio-temporal feature dependencies between target objects and search regions…
DecoderObject TrackingVideo Object TrackingVisual Object Tracking+1Learning Target Candidate Association to Keep Track of What Not to Track
The presence of objects that are confusingly similar to the tracked target, poses a fundamental challenge in appearance-based visual tracking. Such distractor objects are easily misclassified as the target itself, leadin…
Object TrackingVideo Object TrackingVisual Object TrackingVisual TrackingTransformer Tracking
Correlation acts as a critical role in the tracking field, especially in recent popular Siamese-based trackers. The correlation operation is a simple fusion manner to consider the similarity between the template and the …
GPUObject TrackingVideo Object TrackingVisual Object Tracking+1Transformer Meets Tracker: Exploiting Temporal Context for Robust Visual Tracking
In video object tracking, there exist rich temporal contexts among successive frames, which have been largely overlooked in existing trackers. In this work, we bridge the individual video frames and explore the temporal …
DecoderObjectObject TrackingVideo Object Tracking+2