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Found 14 papers, 5 papers with code
UP-Person: Unified Parameter-Efficient Transfer Learning for Text-based Person Retrieval
Text-based Person Retrieval (TPR) as a multi-modal task, which aims to retrieve the target person from a pool of candidate images given a text description, has recently garnered considerable attention due to the progress of contrastive visual-language pre-trained model.
BlobCtrl: A Unified and Flexible Framework for Element-level Image Generation and Editing
Element-level visual manipulation is essential in digital content creation, but current diffusion-based methods lack the precision and flexibility of traditional tools.
BrushEdit: All-In-One Image Inpainting and Editing
Image editing has advanced significantly with the development of diffusion models using both inversion-based and instruction-based methods.
DisPose: Disentangling Pose Guidance for Controllable Human Image Animation
Specifically, we generate a dense motion field from a sparse motion field and the reference image, which provides region-level dense guidance while maintaining the generalization of the sparse pose control.
NVComposer: Boosting Generative Novel View Synthesis with Multiple Sparse and Unposed Images
Recent advancements in generative models have significantly improved novel view synthesis (NVS) from multi-view data.
Image Conductor: Precision Control for Interactive Video Synthesis
To this end, we propose Image Conductor, a method for precise control of camera transitions and object movements to generate video assets from a single image.
Vision-Language Models Meet Meteorology: Developing Models for Extreme Weather Events Detection with Heatmaps
Real-time detection and prediction of extreme weather protect human lives and infrastructure.
Embracing Language Inclusivity and Diversity in CLIP through Continual Language Learning
To alleviate CF raised by covariate shift and lexical overlap, we further propose a novel approach that ensures the identical distribution of all token embeddings during initialization and regularizes token embedding learning during training.
CLIP-based Synergistic Knowledge Transfer for Text-based Person Retrieval
Text-based Person Retrieval (TPR) aims to retrieve the target person images given a textual query.
G2L: Semantically Aligned and Uniform Video Grounding via Geodesic and Game Theory
Due to two annoying issues in video grounding: (1) the co-existence of some visual entities in both ground truth and other moments, \ie semantic overlapping; (2) only a few moments in the video are annotated, \ie sparse annotation dilemma, vanilla contrastive learning is unable to model the correlations between temporally distant moments and learned inconsistent video representations.
Efficient Multimodal Fusion via Interactive Prompting
Large-scale pre-training has brought unimodal fields such as computer vision and natural language processing to a new era.
Unify, Align and Refine: Multi-Level Semantic Alignment for Radiology Report Generation
Automatic radiology report generation has attracted enormous research interest due to its practical value in reducing the workload of radiologists.
Exploiting Auxiliary Caption for Video Grounding
Video grounding aims to locate a moment of interest matching the given query sentence from an untrimmed video.
SIAD: Self-supervised Image Anomaly Detection System
To make a step forward, this paper outlines an automatic annotation system called SsaA, working in a self-supervised learning manner, for continuously making the online visual inspection in the manufacturing automation scenarios.
