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20242026
most citedFrequency Decoupling for Motion Magnification via Multi-Level Isomorphic Architecture

2 citations · 4 across the 19 of their papers we have counts for

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cs.CV2026

Acoustically Grounded Cost Learning for Open-Vocabulary Audio-Visual Semantic Segmentation

Tianrui Hui, Shaofei Huang, Qisong Han +6

Open-Vocabulary Audio-Visual Semantic Segmentation (OV-AVSS) aims to perform pixel-level segmentation of sound-emitting objects from an open set of categories. The previous method…

cs.CV2026

Parse, Search, and Confirmation: Training-Free Aerial Vision-and-Dialog Navigation with Chain-of-Thought Reasoning and Structured Spatial Memory

Yu Qi, Hongyu Li, Shaofei Huang +6

In this paper, we tackle the Aerial Vision-and-Dialog Navigation (AVDN) task in the training-free setting for resource-efficient high-altitude UAV navigation.Naively applying MLLMs…

cs.CV2026

Robust Trajectory Distillation: Hybrid Reweighting Meets Teacher-Inspired Targets

Kaifeng Chen, Lechao Cheng, Jiyang Li +6

Dataset distillation (DD) condenses large corpora into compact, information-rich subsets for efficient training and reuse. However, under noisy supervision, DD risks condensing cor…

cs.CV2026

OmniVL-Guard Pro: A Tool-Augmented Agent for Omnibus Vision-Language Forensics

Jinjie Shen, Zheng Huang, Yuchen Zhang +7

Existing vision-language forgery detection and grounding methods operate under a closed-world paradigm, assuming verification can be completed by the model alone. However, self-con…

cs.CV2026

Multi-Scale Global-Instance Prompt Tuning for Continual Test-time Adaptation in Medical Image Segmentation

Lingrui Li, Yanfeng Zhou, Nan Pu +2

Distribution shift is a common challenge in medical images obtained from different clinical centers, significantly hindering the deployment of pre-trained semantic segmentation mod…

cs.CV2026

OmniVL-Guard: Towards Unified Vision-Language Forgery Detection and Grounding via Balanced RL

Jinjie Shen, Jing Wu, Yaxiong Wang +5

Existing forgery detection methods are often limited to uni-modal or bi-modal settings, failing to handle the interleaved text, images, and videos prevalent in real-world misinform…

cs.CV2025

TDEdit: A Unified Diffusion Framework for Text-Drag Guided Image Manipulation

Qihang Wang, Yaxiong Wang, Lechao Cheng +1

This paper explores image editing under the joint control of text and drag interactions. While recent advances in text-driven and drag-driven editing have achieved remarkable progr…

cs.CV2025

Beyond Artificial Misalignment: Detecting and Grounding Semantic-Coordinated Multimodal Manipulations

Jinjie Shen, Yaxiong Wang, Lechao Cheng +2

The detection and grounding of manipulated content in multimodal data has emerged as a critical challenge in media forensics. While existing benchmarks demonstrate technical progre…

cs.CV2025

SplitGaussian: Reconstructing Dynamic Scenes via Visual Geometry Decomposition

Lechao Cheng, Jiahui Li, Jingxuan He +5

Reconstructing dynamic 3D scenes from monocular video remains fundamentally challenging due to the need to jointly infer motion, structure, and appearance from limited observations…

cs.CV2025

Towards Fine-Grained Emotion Understanding via Skeleton-Based Micro-Gesture Recognition

Hao Xu, Lechao Cheng, Yaxiong Wang +2

We present our solution to the MiGA Challenge at IJCAI 2025, which aims to recognize micro-gestures (MGs) from skeleton sequences for the purpose of hidden emotion understanding. M…

cs.CV2025

SSAM: Self-Supervised Association Modeling for Test-Time Adaption

Yaxiong Wang, Zhenqiang Zhang, Lechao Cheng +3

Test-time adaption (TTA) has witnessed important progress in recent years, the prevailing methods typically first encode the image and the text and design strategies to model the a…

cs.CV2025

Towards Micro-Action Recognition with Limited Annotations: An Asynchronous Pseudo Labeling and Training Approach

Yan Zhang, Lechao Cheng, Yaxiong Wang +2

Micro-Action Recognition (MAR) aims to classify subtle human actions in video. However, annotating MAR datasets is particularly challenging due to the subtlety of actions. To this…

cs.CV2025

Knowledge Swapping via Learning and Unlearning

Mingyu Xing, Lechao Cheng, Shengeng Tang +3

We introduce \textbf{Knowledge Swapping}, a novel task designed to selectively regulate knowledge of a pretrained model by enabling the forgetting of user\-specified information, r…

cs.CV2024

ASAP: Advancing Semantic Alignment Promotes Multi-Modal Manipulation Detecting and Grounding

Zhenxing Zhang, Yaxiong Wang, Lechao Cheng +3

We present ASAP, a new framework for detecting and grounding multi-modal media manipulation (DGM4).Upon thorough examination, we observe that accurate fine-grained cross-modal sema…

cs.CV2024★ 1 cited

EntityCLIP: Entity-Centric Image-Text Matching via Multimodal Attentive Contrastive Learning

Yaxiong Wang, Yujiao Wu, Lianwei Wu +3

Recent advancements in image-text matching have been notable, yet prevailing models predominantly cater to broad queries and struggle with accommodating fine-grained query intentio…

cs.CV2024★ 2 cited

Frequency Decoupling for Motion Magnification via Multi-Level Isomorphic Architecture

Fei Wang, Dan Guo, Kun Li +2

Video Motion Magnification (VMM) aims to reveal subtle and imperceptible motion information of objects in the macroscopic world. Prior methods directly model the motion field from…