Hugging Face Trending Papers
Aug 10

Towards Collaborative Joint Perception and Prediction: Framework, Baseline Evaluation, and Deployment Perspectives

Connected Autonomous Vehicles (CAVs) increasingly exploit Vehicle-to-Everything (V2X) communication to exchange multi-source sensor information, enabling advanced Collaborative Perception (CP) capabilities. Extending beyond these capabilities, this work focuses on Collaborative Joint Perception and Prediction (Co-P&P), a paradigm that unifies CP with motion prediction to mitigate two persistent challenges: the accumulation of perception errors and visual occlusions.

arXiv Computer Vision
Sep 3

BOLT: Online Lightweight Adaptation for Preparation-Free Heterogeneous Cooperative Perception

BOLT is a lightweight plug‑and‑play module that enables preparation‑free heterogeneous cooperative perception by adapting neighboring features online through ego‑as‑teacher distillation. It requires only ego predictions, no ground‑truth labels, and uses high‑confidence ego features to align cross‑agent feature domains while allowing neighbors to contribute in low‑confidence regions. With just 0.9 M trainable parameters, BOLT boosts AP@50 by up to 32.3 points over unadapted fusion and consistently outperforms ego‑only results on DAIR‑V2X and OPV2V.

By Kang Yang, Tianci Bu, Peng Wang, Deying Li, Yongcai Wang
arXiv Computer Vision
Sep 11

MC-DeTra: Motion-Consistent Joint Object Detection and Socially-Aware Trajectory Forecasting in Bird's-Eye-View Images

MC-DeTra is a reimplementation of the DeTra model that jointly performs object detection and socially-aware trajectory forecasting in bird's-eye-view images. It introduces motion-consistency mechanisms that add supervision from each actor’s past motion, surrounding traffic occupancy, and a consistency constraint aligning predicted heading with motion direction. The added losses are train‑only and inference‑safe, improving dynamic trajectory forecasting on the Waymo Open Dataset while maintaining or enhancing detection accuracy.

By Vladislav Diuzhev, Dmitry Yudin