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Lingzhi Li

8 accepted papers

2025

CoDynTrust: Robust Asynchronous Collaborative Perception via Dynamic Feature Trust Modulus

ICRA 2025

Collaborative perception, fusing information from multiple agents, can extend perception range so as to improve perception performance. However, temporal asynchrony in real-world environments, caused by communication delays, clock misalignment, or sampling configuration differences, can lead to info

Cited by 5SourcecodeScholar
2025

INSTINCT: Instance-Level Interaction Architecture for Query-Based Collaborative Perception

ICCV 2025poster

Collaborative perception systems overcome single-vehicle limitations in long-range detection and occlusion scenarios by integrating multi-agent sensory data, improving accuracy and safety. However, frequent cooperative interactions and real-time requirements impose stringent bandwidth constraints. P…

2023

Compressing Volumetric Radiance Fields to 1 MB

CVPR 2023poster

Approximating radiance fields with discretized volumetric grids is one of promising directions for improving NeRFs, represented by methods like DVGO, Plenoxels and TensoRF, which achieve super-fast training convergence and real-time rendering. However, these methods typically require a tremendous st…

2023

DDColor: Towards Photo-Realistic Image Colorization via Dual Decoders

ICCV 2023poster

Image colorization is a challenging problem due to multi-modal uncertainty and high ill-posedness. Directly training a deep neural network usually leads to incorrect semantic colors and low color richness. While transformer-based methods can deliver better results, they often rely on manually design…

Cited by 64PDFcodeScholar
2022

Streaming Radiance Fields for 3D Video Synthesis

NeurIPS 2022accept

We present an explicit-grid based method for efficiently reconstructing streaming radiance fields for novel view synthesis of real world dynamic scenes. Instead of training a single model that combines all the frames, we formulate the dynamic modeling problem with an incremental learning paradigm in…