14 papers
Uncertainty-Aware Consistency Distillation for Few-Step Video Generation
Lingyu Liu, Yaxiong Wang, Li Zhu +1
We study few-step video generation, i.e., distilling a multi-step video generator, which typically requires tens of sampling steps, incurring substantial latency and compute, into…
Pretrain-then-Adapt: Uncertainty-Aware Test-Time Adaptation for Text-based Person Search
Jiahao Zhang, Shaofei Huang, Yaxiong Wang +1
Text-based person search faces inherent limitations due to data scarcity, driven by stringent privacy constraints and the high cost of manual annotation. To mitigate this, existing…
SEED: A Large-Scale Benchmark for Provenance Tracing in Sequential Deepfake Facial Edits
Mengieong Hoi, Zhedong Zheng, Ping Liu +1
Deepfake content on social networks is increasingly produced through multiple \emph{sequential} edits to biometric data such as facial imagery. Consequently, the final appearance o…
Harnessing Weak Pair Uncertainty for Text-based Person Search
Jintao Sun, Zhedong Zheng, Gangyi Ding
In this paper, we study the text-based person search, which is to retrieve the person of interest via natural language description. Prevailing methods usually focus on the strict o…
Can Video Diffusion Models Predict Past Frames? Bidirectional Cycle Consistency for Reversible Interpolation
Lingyu Liu, Yaxiong Wang, Li Zhu +1
Video frame interpolation aims to synthesize realistic intermediate frames between given endpoints while adhering to specific motion semantics. While recent generative models have…
Look, Compare and Draw: Differential Query Transformer for Automatic Oil Painting
Lingyu Liu, Yaxiong Wang, Li Zhu +2
This work introduces a new approach to automatic oil painting that emphasizes the creation of dynamic and expressive brushstrokes. A pivotal challenge lies in mitigating the duplic…
Cultivating Forensic Reasoning for Generalizable Multimodal Manipulation Detection
Yuchen Zhang, Yaxiong Wang, Kecheng Han +4
Recent advances in generative AI have significantly enhanced the realism of multimodal media manipulation, thereby posing substantial challenges to manipulation detection. Existing…
Minimizing the Pretraining Gap: Domain-aligned Text-Based Person Retrieval
Shuyu Yang, Yaxiong Wang, Yongrui Li +2
In this work, we focus on text-based person retrieval, which identifies individuals based on textual descriptions. Despite advancements enabled by synthetic data for pretraining, a…
Towards Scalable Video Anomaly Retrieval: A Synthetic Video-Text Benchmark
Shuyu Yang, Yilun Wang, Yaxiong Wang +2
Video anomaly retrieval aims to localize anomalous events in videos using natural language queries to facilitate public safety. However, existing datasets suffer from severe limita…
TIGeR: Text-Instructed Generation and Refinement for Template-Free Hand-Object Interaction
Yiyao Huang, Zhedong Zheng, Yu Ziwei +3
Pre-defined 3D object templates are widely used in 3D reconstruction of hand-object interactions. However, they often require substantial manual efforts to capture or source, and i…
Scale Up Composed Image Retrieval Learning via Modification Text Generation
Yinan Zhou, Yaxiong Wang, Haokun Lin +3
Composed Image Retrieval (CIR) aims to search an image of interest using a combination of a reference image and modification text as the query. Despite recent advancements, this ta…
Every Painting Awakened: A Training-free Framework for Painting-to-Animation Generation
Lingyu Liu, Yaxiong Wang, Li Zhu +1
We introduce a training-free framework specifically designed to bring real-world static paintings to life through image-to-video (I2V) synthesis, addressing the persistent challeng…
Generating Attribution Reports for Manipulated Facial Images: A Dataset and Baseline
Jingchun Lian, Lingyu Liu, Yaxiong Wang +4
Existing facial forgery detection methods typically focus on binary classification or pixel-level localization, providing little semantic insight into the nature of the manipulatio…
Beyond Walking: A Large-Scale Image-Text Benchmark for Text-based Person Anomaly Search
Shuyu Yang, Yaxiong Wang, Li Zhu +1
Text-based person search aims to retrieve specific individuals across camera networks using natural language descriptions. However, current benchmarks often exhibit biases towards…