Papers Video Object Tracking
“Video Object Tracking” 태그가 달린 논문 107편 · 필터 해제
Hopper: Multi-hop Transformer for Spatiotemporal Reasoning
This paper considers the problem of spatiotemporal object-centric reasoning in videos. Central to our approach is the notion of object permanence, i.e., the ability to reason about the location of objects as they move th…
ObjectVideo Object TrackingTDIOT: Target-driven Inference for Deep Video Object Tracking
Recent tracking-by-detection approaches use deep object detectors as target detection baseline, because of their high performance on still images. For effective video object tracking, object detection is integrated with …
Objectobject-detectionObject DetectionObject Tracking+2End-to-end Deep Object Tracking with Circular Loss Function for Rotated Bounding Box
The task object tracking is vital in numerous applications such as autonomous driving, intelligent surveillance, robotics, etc. This task entails the assigning of a bounding box to an object in a video stream, given only…
Autonomous DrivingDeep LearningObjectObject Tracking+1Attention over learned object embeddings enables complex visual reasoning
Neural networks have achieved success in a wide array of perceptual tasks but often fail at tasks involving both perception and higher-level reasoning. On these more challenging tasks, bespoke approaches (such as modular…
ObjectVideo Object TrackingVisual ReasoningContrastive Transformation for Self-supervised Correspondence Learning
In this paper, we focus on the self-supervised learning of visual correspondence using unlabeled videos in the wild. Our method simultaneously considers intra- and inter-video representation associations for reliable cor…
Object TrackingSelf-Supervised LearningSemantic SegmentationVideo Object Segmentation+2Learning to Fuse Asymmetric Feature Maps in Siamese Trackers
Recently, Siamese-based trackers have achieved promising performance in visual tracking. Most recent Siamese-based trackers typically employ a depth-wise cross-correlation (DW-XCorr) to obtain multi-channel correlation i…
Video Object TrackingVisual Object TrackingVisual TrackingApproxDet: Content and Contention-Aware Approximate Object Detection for Mobiles
Advanced video analytic systems, including scene classification and object detection, have seen widespread success in various domains such as smart cities and autonomous transportation. With an ever-growing number of pow…
Objectobject-detectionObject DetectionObject Tracking+3Fast Video Object Segmentation With Temporal Aggregation Network and Dynamic Template Matching
Significant progress has been made in Video Object Segmentation (VOS), the video object tracking task in its finest level. While the VOS task can be naturally decoupled into image semantic segmentation and video object t…
ObjectObject TrackingOne-Shot LearningSegmentation+6Tracking-by-Trackers with a Distilled and Reinforced Model
Visual object tracking was generally tackled by reasoning independently on fast processing algorithms, accurate online adaptation methods, and fusion of trackers. In this paper, we unify such goals by proposing a novel t…
Knowledge DistillationObject TrackingVideo Object TrackingVisual Object Tracking+1Ocean: Object-aware Anchor-free Tracking
Anchor-based Siamese trackers have achieved remarkable advancements in accuracy, yet the further improvement is restricted by the lagged tracking robustness. We find the underlying reason is that the regression network i…
ObjectVideo Object TrackingVisual Object TrackingFast Template Matching and Update for Video Object Tracking and Segmentation
In this paper, the main task we aim to tackle is the multi-instance semi-supervised video object segmentation across a sequence of frames where only the first-frame box-level ground-truth is provided. Detection-based alg…
Object Trackingreinforcement-learningReinforcement LearningReinforcement Learning (RL)+6Know Your Surroundings: Exploiting Scene Information for Object Tracking
Current state-of-the-art trackers only rely on a target appearance model in order to localize the object in each frame. Such approaches are however prone to fail in case of e.g. fast appearance changes or presence of dis…
Object TrackingVideo Object TrackingLearning Object Permanence from Video
Object Permanence allows people to reason about the location of non-visible objects, by understanding that they continue to exist even when not perceived directly. Object Permanence is critical for building a model of th…
ObjectVideo Object TrackingArgus: Efficient Activity Detection System for Extended Video Analysis
We propose an Efficient Activity Detection System, Argus, for Extended Video Analysis in the surveillance scenario. For the spatial-temporal event detection in the surveillance video, we first generate video proposals by…
Action DetectionActivity DetectionEvent DetectionMulti-Object Tracking+5Integration of Regularized l1 Tracking and Instance Segmentation for Video Object Tracking
We introduce a tracking-by-detection method that integrates a deep object detector with a particle filter tracker under the regularization framework where the tracked object is represented by a sparse dictionary. A novel…
BenchmarkingInstance SegmentationObjectObject Tracking+3Improving Human Annotation in Single Object Tracking
Human annotation is always considered as ground truth in video object tracking tasks. It is used in both training and evaluation purposes. Thus, ensuring its high quality is an important task for the success of trackers …
ObjectObject TrackingVideo Object TrackingSPARK: Spatial-aware Online Incremental Attack Against Visual Tracking
Adversarial attacks of deep neural networks have been intensively studied on image, audio, natural language, patch, and pixel classification tasks. Nevertheless, as a typical, while important real-world application, the …
Adversarial AttackObject TrackingVideo Object TrackingVisual Object Tracking+1CATER: A diagnostic dataset for Compositional Actions and TEmporal Reasoning
Computer vision has undergone a dramatic revolution in performance, driven in large part through deep features trained on large-scale supervised datasets. However, much of these improvements have focused on static image …
DiagnosticObjectVideo Object TrackingVideo UnderstandingA Comparison of CNN and Classic Features for Image Retrieval
Feature detectors and descriptors have been successfully used for various computer vision tasks, such as video object tracking and content-based image retrieval. Many methods use image gradients in different stages of th…
Content-Based Image RetrievalImage RetrievalKeypoint DetectionObject Tracking+2DAWN: Dual Augmented Memory Network for Unsupervised Video Object Tracking
Psychological studies have found that human visual tracking system involves learning, memory, and planning. Despite recent successes, not many works have focused on memory and planning in deep learning based tracking. We…
Object TrackingVideo Object TrackingVisual Tracking