Ming Li

25

Papers

239

Total Citations

Papers (25)

ControlNet++: Improving Conditional Controls with Efficient Consistency Feedback

When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline

Synthetic-to-Real Self-supervised Robust Depth Estimation via Learning with Motion and Structure Priors

MDP3: A Training-free Approach for List-wise Frame Selection in Video-LLMs

SuperEdit: Rectifying and Facilitating Supervision for Instruction-Based Image Editing

EventGPT: Event Stream Understanding with Multimodal Large Language Models

EEE-Bench: A Comprehensive Multimodal Electrical And Electronics Engineering Benchmark

ML-GOOD: Towards Multi-Label Graph Out-Of-Distribution Detection

DHAKR: Learning Deep Hierarchical Attention-Based Kernelized Representations for Graph Classification

AUC Optimization from Multiple Unlabeled Datasets

PVChat: Personalized Video Chat with One-Shot Learning

HiFi-Portrait: Zero-shot Identity-preserved Portrait Generation with High-fidelity Multi-face Fusion

SPADE: Spatial-Aware Denoising Network for Open-vocabulary Panoptic Scene Graph Generation with Long- and Local-range Context Reasoning

L3A: Label-Augmented Analytic Adaptation for Multi-Label Class Incremental Learning

QBMK: Quantum-based Matching Kernels for Un-attributed Graphs

ProJudge: A Multi-Modal Multi-Discipline Benchmark and Instruction-Tuning Dataset for MLLM-based Process Judges

EFTViT: Efficient Federated Training of Vision Transformers with Masked Images on Resource-Constrained Clients

FedVLA: Federated Vision-Language-Action Learning with Dual Gating Mixture-of-Experts for Robotic Manipulation

Multimodal Contrastive Learning for Cybersickness Recognition Using Brain Connectivity Graph Representation

EEG2Gaussian: Decoding and Visualizing Visual-Evoked EEG for VR Scenes Using 3D Gaussian Splatting

Zero-shot Video Moment Retrieval via Off-the-shelf Multimodal Large Language Models

Deep Hypergraph Neural Networks with Tight Framelets

Slice-and-Pack: Tailoring Deep Models for Customized Requirements

Ambiguity-Aware Abductive Learning

How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing