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Found 8 papers, 5 papers with code
Quo Vadis: Is Trajectory Forecasting the Key Towards Long-Term Multi-Object Tracking?
While we have significantly advanced short-term tracking performance, bridging longer occlusion gaps remains elusive: state-of-the-art object trackers only bridge less than 10% of occlusions longer than three seconds.
MOTCOM: The Multi-Object Tracking Dataset Complexity Metric
There exists no comprehensive metric for describing the complexity of Multi-Object Tracking (MOT) sequences.
MG-GAN: A Multi-Generator Model Preventing Out-of-Distribution Samples in Pedestrian Trajectory Prediction
Pedestrian trajectory prediction is challenging due to its uncertain and multimodal nature.
MOTChallenge: A Benchmark for Single-Camera Multiple Target Tracking
We present MOTChallenge, a benchmark for single-camera Multiple Object Tracking (MOT) launched in late 2014, to collect existing and new data, and create a framework for the standardized evaluation of multiple object tracking methods.
Goal-GAN: Multimodal Trajectory Prediction Based on Goal Position Estimation
Inspired by human navigation, we model the task of trajectory prediction as an intuitive two-stage process: (i) goal estimation, which predicts the most likely target positions of the agent, followed by a (ii) routing module which estimates a set of plausible trajectories that route towards the estimated goal.
HOTA: A Higher Order Metric for Evaluating Multi-Object Tracking
Multi-Object Tracking (MOT) has been notoriously difficult to evaluate.
MOT20: A benchmark for multi object tracking in crowded scenes
The benchmark for Multiple Object Tracking, MOTChallenge, was launched with the goal to establish a standardized evaluation of multiple object tracking methods.
Multi-Object Tracking
Multiple Object Tracking with Transformer
+2
CVPR19 Tracking and Detection Challenge: How crowded can it get?
Standardized benchmarks are crucial for the majority of computer vision applications.
