SOTAVerified

Visual Object Tracking

Visual Object Tracking is an important research topic in computer vision, image understanding and pattern recognition. Given the initial state (centre location and scale) of a target in the first frame of a video sequence, the aim of Visual Object Tracking is to automatically obtain the states of the object in the subsequent video frames.

Source: Learning Adaptive Discriminative Correlation Filters via Temporal Consistency Preserving Spatial Feature Selection for Robust Visual Object Tracking

Papers

Showing 126150 of 341 papers

TitleStatusHype
Fast and Accurate Online Video Object Segmentation via Tracking PartsCode0
SegFlow: Joint Learning for Video Object Segmentation and Optical FlowCode0
Semi-Automatic Annotation For Visual Object TrackingCode0
CGTrack: Cascade Gating Network with Hierarchical Feature Aggregation for UAV TrackingCode0
AViTMP: A Tracking-Specific Transformer for Single-Branch Visual TrackingCode0
SPARK: Spatial-aware Online Incremental Attack Against Visual TrackingCode0
Robust Visual Tracking using Multi-Frame Multi-Feature Joint ModelingCode0
Rotation Adaptive Visual Object Tracking with Motion ConsistencyCode0
Event-based Visual Tracking in Dynamic EnvironmentsCode0
An equalised global graphical model-based approach for multi-camera object trackingCode0
CapsuleVOS: Semi-Supervised Video Object Segmentation Using Capsule RoutingCode0
Learning Discriminative Model Prediction for TrackingCode0
EgoTracks: A Long-term Egocentric Visual Object Tracking DatasetCode0
Boundary Effect-Aware Visual Tracking for UAV with Online Enhanced Background Learning and Multi-Frame Consensus VerificationCode0
Efficient Visual Tracking with Exemplar TransformersCode0
Efficient Video Object Segmentation via Network ModulationCode0
Robust Estimation of Similarity Transformation for Visual Object TrackingCode0
Reliable Object Tracking by Multimodal Hybrid Feature Extraction and Transformer-Based FusionCode0
Beyond Correlation Filters: Learning Continuous Convolution Operators for Visual TrackingCode0
ECO: Efficient Convolution Operators for TrackingCode0
Siamese Natural Language Tracker: Tracking by Natural Language Descriptions with Siamese TrackersCode0
Spatially Supervised Recurrent Convolutional Neural Networks for Visual Object TrackingCode0
Distractor-aware Siamese Networks for Visual Object TrackingCode0
Discriminative Correlation Filter with Channel and Spatial ReliabilityCode0
Discriminative and Robust Online Learning for Siamese Visual TrackingCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1SPMTrack-GAUC77.4Unverified
2SPMTrack-LAUC76.8Unverified
3MCITrack-L384AUC76.6Unverified
4LoRAT-g-378AUC76.2Unverified
5MCITrack-B224AUC75.3Unverified
6DAM4SAMAUC75.1Unverified
7LoRAT-L-378AUC75.1Unverified
8SPMTrack-BAUC74.9Unverified
9RTracker-LAUC74.7Unverified
10SAMURAI-LAUC74.2Unverified
#ModelMetricClaimedVerifiedStatus
1SAMURAI-LAverage Overlap81.7Unverified
2DAM4SAMAverage Overlap81.1Unverified
3SPMTrack-GAverage Overlap81Unverified
4MITSAverage Overlap80.4Unverified
5MCITrack-L384Average Overlap80Unverified
6SPMTrack-LAverage Overlap80Unverified
7ARTrackV2-LAverage Overlap79.5Unverified
8LoRAT-g-378Average Overlap78.9Unverified
9ARTrack-LAverage Overlap78.5Unverified
10ODTrack-LAverage Overlap78.2Unverified
#ModelMetricClaimedVerifiedStatus
1DropTrackNormalized Precision88.9Unverified
2MCITrack-L384Accuracy87.9Unverified
3SPMTrack-GAccuracy87.3Unverified
4SPMTrack-LAccuracy86.9Unverified
5MCITrack-B224Accuracy86.3Unverified
6ODTrack-LAccuracy86.1Unverified
7ARTrackV2-LAccuracy86.1Unverified
8SPMTrack-BAccuracy86.1Unverified
9MixViT-L(ConvMAE)Accuracy86.1Unverified
10LoRAT-g-378Accuracy86Unverified
#ModelMetricClaimedVerifiedStatus
1SAMURAI-LAUC61Unverified
2DAM4SAMAUC60.9Unverified
3LoRAT-L-378AUC56.6Unverified
4LoRAT-g-378AUC56.5Unverified
5UNINEXT-HAUC56.2Unverified
6MCITrack-L384AUC55.7Unverified
7RTracker-LAUC54.9Unverified
8MCITrack-B224AUC54.6Unverified
9ODTrack-LAUC53.9Unverified
10ARTrackV2-LAUC53.4Unverified
#ModelMetricClaimedVerifiedStatus
1GradNetPrecision0.86Unverified
2SPMTrack-BAUC0.73Unverified
3ODTrack-LAUC0.72Unverified
4ODTrack-BAUC0.72Unverified
5STMTrackAUC0.72Unverified
6SAMURAI-LAUC0.72Unverified
7PiVOT-LAUC0.71Unverified
8HIPTrackAUC0.71Unverified
9KeepTrackAUC0.71Unverified
10TRASFUSTAUC0.7Unverified
#ModelMetricClaimedVerifiedStatus
1LoRAT-g-378AUC0.74Unverified
2NeighborTrack-OSTrackAUC0.73Unverified
3LoRAT-L-378AUC0.73Unverified
4SPMTrack-BAUC0.72Unverified
5ARTrackV2-LAUC0.72Unverified
6ARTrack-LAUC0.71Unverified
7OSTrack -384AUC0.71Unverified
8AiATrackAUC0.71Unverified
9HIPTrackAUC0.71Unverified
10MixFormerAUC0.7Unverified
#ModelMetricClaimedVerifiedStatus
1MCITrack-L384AUC65.3Unverified
2SPMTrack-GAUC64.7Unverified
3SPMTrack-LAUC63.7Unverified
4MCITrack-B224AUC62.9Unverified
5LoRAT-g-378AUC62.7Unverified
6LoRAT-L-378AUC62.3Unverified
7SPMTrack-BAUC62Unverified
8ODTrack-LAUC61.7Unverified
9ARTrackV2-LAUC61.6Unverified
10ODTrack-BAUC60.9Unverified
#ModelMetricClaimedVerifiedStatus
1SiamMask_EExpected Average Overlap (EAO)0.45Unverified
2SiamFC++Expected Average Overlap (EAO)0.43Unverified
3SiamRPN++_RExpected Average Overlap (EAO)0.42Unverified
4THOR-SiamRPNExpected Average Overlap (EAO)0.42Unverified
5SiamRPN++Expected Average Overlap (EAO)0.41Unverified
6THOR-SiamMaskExpected Average Overlap (EAO)0.41Unverified