activity
20232026
most citedDynamic Sub-graph Distillation for Robust Semi-supervised Continual Learning

12 citations · 19 across the 31 of their papers we have counts for

collaborators

39 papers

cs.CV2026

Destination-Conditioned Adaptation with Semantic-Geometric Alignment for Generative Inbetweening

Zhiyu Xu, Wei Shang, Yushen Xu +4

Generative inbetweening aims to synthesize temporally coherent intermediate frames between a start frame and a target frame. Although pretrained image-to-video diffusion models pro…

cs.LG2026

Topology-Adaptive Hyperbolic Graph Attention Networks Guided by the Hyperbolic Sombor Index

Haifang Cao, Boan Tao, Xiyuan Gao +3

Hyperbolic geometry has emerged as a principled space for representing hierarchical graphs. However, existing hyperbolic graph neural networks typically rely on shared curvature co…

cs.CV2026

SAGE: Source-Anchored Guidance via Frequency Equalization for Hierarchical RGB-T Alignment and Fusion

Timing Li, Yiming Sun, Boan Tao +3

Spatial misregistration and cross-modal discrepancies often cause ghosting, structural blurring, and content imbalance in RGB-T fusion. Existing methods typically decouple appearan…

cs.CV2026

Socialized UAV Cross-Task Learning: Towards Cross-Granularity Collaboration through Hierarchical Interaction

Xinjie Yao, Ruipu Zhao, Yunqi Zhu +6

Joint learning across heterogeneous tasks is often treated as task coupling through feature sharing, distillation, or auxiliary supervision. However, in cross-task learning, mismat…

cs.CV2026

UniDiffFusion: A Unified Diffusion Framework for Multi-Task and Degradation-Robust Image Fusion

Xingxin Xu, Siqi Zhao, Xin Li +3

General image fusion aims to integrate complementary information from multiple source images, but existing methods often rely on task-specific models and struggle to maintain robus…

cs.CV2026

Socialized Detector Learning: Trajectory-Guided and Reciprocal Distillation for Heterogeneous Object Detectors

Weihao Li, Yunqi Zhu, Zhihe Fan +5

Object detection knowledge is fragmented across independently trained, heterogeneous detectors with complementary category supports. In socialized learning, this knowledge resides…

cs.RO2026

RACO: Reliability-Aware Coarse-Goal Optimization for Inspection-Oriented UAV Vision-Language Navigation

Sen Wang, Yiming Sun, Jiaxuan He +1

UAV vision-language navigation (UAV-VLN) is commonly evaluated as goal reaching, but inspection-oriented deployment requires the agent to stop within a valid inspection region and…

cs.AI2026

Socialized Division and Collaboration: Rethinking Class-Incremental Learning under Optimization Conflicts

Xinjie Yao, Zhihe Fan, Yunqi Zhu +6

Class-incremental learning is commonly instantiated as a single-model paradigm, where a unified model sequentially adapts to an unbounded stream of sessions. While effective under…

cs.CV2026

DynCur-Geo: Dynamic Curiosity Reward Shaping for Multimodal Active Geo-Localization

Yiming Sun, Yang Zhang, Pengfei Zhu

Active geo-localization enables low-altitude UAVs to search for specified targets from limited local aerial observations, supporting time-sensitive applications such as search and…

cs.AI2026

Towards a new paradigm of scientific discovery with socialized artificial intelligence

Xinjie Yao, Xingxin Xu, Xiyuan Gao +21

Scientific discovery has advanced through successive transformations in the organization of knowledge. Observation and experimentation established the empirical foundations of scie…

cs.LG2026

Geometric Mixture-of-Experts with Curvature-Guided Adaptive Routing for Graph Representation Learning

Haifang Cao, Yu Wang, Timing Li +2

Graph-structured data typically exhibits complex topological heterogeneity, making it difficult to model accurately within a single Riemannian manifold. While emerging mixed-curvat…

cs.CV2026

RGBX-R1: Visual Modality Chain-of-Thought Guided Reinforcement Learning for Multimodal Grounding

Jiahe Wu, Bing Cao, Qilong Wang +3

Multimodal Large Language Models (MLLM) are primarily pre-trained on the RGB modality, thereby limiting their performance on other modalities, such as infrared, depth, and event da…

cs.CV2026

Reversible Efficient Diffusion for Image Fusion

Xingxin Xu, Bing Cao, DongDong Li +2

Multi-modal image fusion aims to consolidate complementary information from diverse source images into a unified representation. The fused image is expected to preserve fine detail…

cs.CV2026

CtrlFuse: Mask-Prompt Guided Controllable Infrared and Visible Image Fusion

Yiming Sun, Yuan Ruan, Qinghua Hu +1

Infrared and visible image fusion generates all-weather perception-capable images by combining complementary modalities, enhancing environmental awareness for intelligent unmanned…

cs.CV2026

DIFF-MF: A Difference-Driven Channel-Spatial State Space Model for Multi-Modal Image Fusion

Yiming Sun, Zifan Ye, Qinghua Hu +1

Multi-modal image fusion aims to integrate complementary information from multiple source images to produce high-quality fused images with enriched content. Although existing appro…

cs.CV2025

Simpler and Stronger Baselines for All-in-One Image Restoration

Hongyu Du, Wenlong Jiao, Heyang Lee +7

Current methods for all-in-one image restoration increasingly rely on complex mechanisms, such as Mixture-of-Experts or prompt learning, to handle diverse degradations.In this work…

cs.CV2025

BasicAVSR: Arbitrary-Scale Video Super-Resolution via Image Priors and Enhanced Motion Compensation

Wei Shang, Wanying Zhang, Shuhang Gu +3

Arbitrary-scale video super-resolution (AVSR) aims to enhance the resolution of video frames, potentially at various scaling factors, which presents several challenges regarding sp…

cs.CV2025

Decoupled Multi-Predictor Optimization for Inference-Efficient Model Tuning

Liwei Luo, Shuaitengyuan Li, Dongwei Ren +3

Recently, remarkable progress has been made in large-scale pre-trained model tuning, and inference efficiency is becoming more crucial for practical deployment. Early exiting in co…

cs.LG2025

Multimodal Negative Learning

Baoquan Gong, Xiyuan Gao, Pengfei Zhu +2

Multimodal learning systems often encounter challenges related to modality imbalance, where a dominant modality may overshadow others, thereby hindering the learning of weak modali…

cs.CV2025

Motion-Aware Adaptive Pixel Pruning for Efficient Local Motion Deblurring

Wei Shang, Dongwei Ren, Wanying Zhang +3

Local motion blur in digital images originates from the relative motion between dynamic objects and static imaging systems during exposure. Existing deblurring methods face signifi…

cs.CV2025

Hyperbolic Cycle Alignment for Infrared-Visible Image Fusion

Timing Li, Bing Cao, Jiahe Feng +3

Image fusion synthesizes complementary information from multiple sources, mitigating the inherent limitations of unimodal imaging systems. Accurate image registration is essential…

cs.CV2025

High-Frequency Prior-Driven Adaptive Masking for Accelerating Image Super-Resolution

Wei Shang, Dongwei Ren, Wanying Zhang +3

The primary challenge in accelerating image super-resolution lies in reducing computation while maintaining performance and adaptability. Motivated by the observation that high-fre…

cs.CV2025

Bi-directional Self-Registration for Misaligned Infrared-Visible Image Fusion

Timing Li, Bing Cao, Pengfei Zhu +2

Acquiring accurately aligned multi-modal image pairs is fundamental for achieving high-quality multi-modal image fusion. To address the lack of ground truth in current multi-modal…

cs.CV2025

VTD-CLIP: Video-to-Text Discretization via Prompting CLIP

Wencheng Zhu, Yuexin Wang, Hongxuan Li +2

Vision-language models bridge visual and linguistic understanding and have proven to be powerful for video recognition tasks. Existing approaches primarily rely on parameter-effici…