4 accepted papers
Benchmarking autonomous driving planners to align with human judgment remains a critical challenge, as state-of-the-art metrics like the Extended Predictive Driver Model Score (EPDMS) lack context awareness in nuanced scenarios. To address this, we introduce DriveCritic, a novel framework featuring …
Many modern AI systems are designed to operate under diverse, open-ended, use-cases. To help generalize deployed systems, developers rely on a reactive AI flywheel that observes emerging feedback from user behavior (errors) and patches the model accordingly. However, most flywheels ignore the broade…
In this work, we present an end-to-end framework for camera-based 3D multi-object tracking, called DQTrack. To avoid heuristic design in detection-based trackers, recent query-based approaches deal with identity-agnostic detection and identity-aware tracking in a single embedding. However, it brings…
"Structured channel pruning has been shown to significantly accelerate inference time for convolution neural networks (CNNs) on modern hardware, with a relatively minor loss of network accuracy. Recent works permanently zero these channels during training, which we observe to significantly hamper fi…