FactorJEPA splits a video prediction model into layout, agent, and interaction channels with a visibility gate, and a new DENSEWORLD dataset tests it on crowded Indian city scenes.
Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking
7 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
abstract
To help accelerate progress in multi-target, multi-camera tracking systems, we present (i) a new pair of precision-recall measures of performance that treats errors of all types uniformly and emphasizes correct identification over sources of error; (ii) the largest fully-annotated and calibrated data set to date with more than 2 million frames of 1080p, 60fps video taken by 8 cameras observing more than 2,700 identities over 85 minutes; and (iii) a reference software system as a comparison baseline. We show that (i) our measures properly account for bottom-line identity match performance in the multi-camera setting; (ii) our data set poses realistic challenges to current trackers; and (iii) the performance of our system is comparable to the state of the art.
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unclear 1representative citing papers
NOOUGAT unifies online and offline multi-object tracking with a GNN that processes non-overlapping subclips fused by an Autoregressive Long-term Tracking layer, reporting SOTA gains on DanceTrack, SportsMOT, and MOT20.
Adding a Deep InfoMax-style adversarial loss to IDE and PCB person re-identification baselines gives modest rank-1/mAP gains, but the claimed mutual information between input image and encoder output is not implemented as stated.
PH-GCN constructs a hierarchical graph of person parts and performs local/global feature learning via message passing in an end-to-end network for person re-identification.
A survey of causal reasoning for video person re-identification that reviews DIR-ReID, identity-shuffle GANs, and causal transformers, but contains unverified performance claims.
A YOLOv8-ByteTrack pipeline plus stereo triangulation can produce 3D fish tracks for some underwater video pairs, but the claimed multi-view accuracy improvement is not demonstrated.
citing papers explorer
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FactorJEPA: Factorizing Monolithic Futures into Layout-Agent-Interaction Channels for Crowded and Chaotic Global South Urban Worlds
FactorJEPA splits a video prediction model into layout, agent, and interaction channels with a visibility gate, and a new DENSEWORLD dataset tests it on crowded Indian city scenes.
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NOOUGAT: Towards Unified Online and Offline Multi-Object Tracking
NOOUGAT unifies online and offline multi-object tracking with a GNN that processes non-overlapping subclips fused by an Autoregressive Long-term Tracking layer, reporting SOTA gains on DanceTrack, SportsMOT, and MOT20.
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Learning Deep Representations by Mutual Information for Person Re-identification
Adding a Deep InfoMax-style adversarial loss to IDE and PCB person re-identification baselines gives modest rank-1/mAP gains, but the claimed mutual information between input image and encoder output is not implemented as stated.
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PH-GCN: Person Re-identification with Part-based Hierarchical Graph Convolutional Network
PH-GCN constructs a hierarchical graph of person parts and performs local/global feature learning via message passing in an end-to-end network for person re-identification.
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Causality and "In-the-Wild" Video-Based Person Re-ID: A Survey
A survey of causal reasoning for video person re-identification that reviews DIR-ReID, identity-shuffle GANs, and causal transformers, but contains unverified performance claims.
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A Framework for Multi-View Multiple Object Tracking using Single-View Multi-Object Trackers on Fish Data
A YOLOv8-ByteTrack pipeline plus stereo triangulation can produce 3D fish tracks for some underwater video pairs, but the claimed multi-view accuracy improvement is not demonstrated.
- ByteTraX: Enhancing the ByteTrack Architecture with Optimised Thresholding