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Jinglin Liang

5 accepted papers

2026

SegPVSG: Panoptic Video Scene Graph Generation via Temporal Focusing and Generative Augmentation

ICML 2026poster

Panoptic Video Scene Graph Generation (PVSG) aims to identify relations between pixel-level entities in a video, serving as a novel paradigm for structured video parsing. However, this task faces two key challenges. First, the interactions between entities are temporally fragmented and sparse, meani…

Cited by 0SourceScholar
2026

VDE: Training-Free Accelerating Rectified Flow Model via Velocity Decomposition and Estimation

CVPR 2026

Though rectified flow models have achieved remarkable performance in image, video, and 3D generation, their practical deployments are challenged by slow inference speeds. Prior acceleration methods reuse cached features from previous steps, which neglects the growing mismatch between static caches a

Cited by 0SourcecodeScholar
2025

Order-Level Attention Similarity Across Language Models: A Latent Commonality

NeurIPS 2025poster

In this paper, we explore an important yet previously neglected question: Do context aggregation patterns across Language Models (LMs) share commonalities? While some works have investigated context aggregation or attention weights in LMs, they typically focus on individual models or attention heads…

Cited by 0SourcecodeScholar
2025

ReplayCAD: Generative Diffusion Replay for Continual Anomaly Detection

IJCAI 2025

Continual Anomaly Detection (CAD) enables anomaly detection models in learning new classes while preserving knowledge of historical classes. CAD faces two key challenges: catastrophic forgetting and segmentation of small anomalous regions. Existing CAD methods store image distributions or patch feat

2024

Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning

ECCV 2024oral

"Federated Class Continual Learning (FCCL) merges the challenges of distributed client learning with the need for seamless adaptation to new classes without forgetting old ones. The key challenge in FCCL is catastrophic forgetting, an issue that has been explored to some extent in Continual Learning…