HyperAI

Visual Object Tracking On Got 10K

Métriques

Average Overlap
Success Rate 0.5
Success Rate 0.75

Résultats

Résultats de performance de divers modèles sur ce benchmark

Nom du modèle
Average Overlap
Success Rate 0.5
Success Rate 0.75
Paper TitleRepository
SLT-TransT67.576.860.3Towards Sequence-Level Training for Visual Tracking
OSTrack-38473.783.270.8Joint Feature Learning and Relation Modeling for Tracking: A One-Stream Framework
MCITrack-B22477.988.276.8Exploring Enhanced Contextual Information for Video-Level Object Tracking
MCITrack-L38480.088.580.2Exploring Enhanced Contextual Information for Video-Level Object Tracking
DiMP61.171.7-Learning Discriminative Model Prediction for Tracking
SeqTrack-L38474.881.972.2Unified Sequence-to-Sequence Learning for Single- and Multi-Modal Visual Object Tracking
Siam R-CNN64.972.8-Siam R-CNN: Visual Tracking by Re-Detection-
MITS80.489.875.8Integrating Boxes and Masks: A Multi-Object Framework for Unified Visual Tracking and Segmentation
STMTrack64.273.757.5STMTrack: Template-free Visual Tracking with Space-time Memory Networks
ATOM61.074.2-ATOM: Accurate Tracking by Overlap Maximization
ARTrackV2-L79.587.879.6ARTrackV2: Prompting Autoregressive Tracker Where to Look and How to Describe
TRASFUST61.772.9-Tracking-by-Trackers with a Distilled and Reinforced Model
NeighborTrack-OSTrack75.785.7273.3NeighborTrack: Improving Single Object Tracking by Bipartite Matching with Neighbor Tracklets
ARTrack-L78.587.477.8Autoregressive Visual Tracking
FEAR-M62.3--FEAR: Fast, Efficient, Accurate and Robust Visual Tracker
SAMURAI-L81.792.276.9SAMURAI: Adapting Segment Anything Model for Zero-Shot Visual Tracking with Motion-Aware Memory-
TATrack-L-GOT76.685.773.4Target-Aware Tracking with Long-term Context Attention-
Ocean61.172.1-Ocean: Object-aware Anchor-free Tracking
MixFormer-1k71.279.965.8MixFormer: End-to-End Tracking with Iterative Mixed Attention
FEAR-L64.5--FEAR: Fast, Efficient, Accurate and Robust Visual Tracker
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