most cited-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding

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cs.CV2025

Spatial-Temporal Pre-Training for Embryo Viability Prediction Using Time-Lapse Videos

Zhiyi Shi, Junsik Kim, Helen Y. Yang +5

Automating embryo viability prediction for in vitro fertilization (IVF) is important but challenging due to the limited availability of labeled pregnancy outcome data, as only a sm…

cs.CV2025

DualEdit: Dual Editing for Knowledge Updating in Vision-Language Models

Zhiyi Shi, Binjie Wang, Chongjie Si +3

Model editing aims to efficiently update a pre-trained model's knowledge without the need for time-consuming full retraining. While existing pioneering editing methods achieve prom…

cs.CV2024

Affordance-Aware Object Insertion via Mask-Aware Dual Diffusion

Jixuan He, Wanhua Li, Ye Liu +3

As a common image editing operation, image composition involves integrating foreground objects into background scenes. In this paper, we expand the application of the concept of Af…

cs.CV2024

Multimodal Learning for Embryo Viability Prediction in Clinical IVF

Junsik Kim, Zhiyi Shi, Davin Jeong +8

In clinical In-Vitro Fertilization (IVF), identifying the most viable embryo for transfer is important to increasing the likelihood of a successful pregnancy. Traditionally, this p…

cs.CV2024

Is What You Ask For What You Get? Investigating Concept Associations in Text-to-Image Models

Salma Abdel Magid, Weiwei Pan, Simon Warchol +4

Text-to-image (T2I) models are increasingly used in impactful real-life applications. As such, there is a growing need to audit these models to ensure that they generate desirable,…

cs.CV2024

MoRA: LoRA Guided Multi-Modal Disease Diagnosis with Missing Modality

Zhiyi Shi, Junsik Kim, Wanhua Li +2

Multi-modal pre-trained models efficiently extract and fuse features from different modalities with low memory requirements for fine-tuning. Despite this efficiency, their applicat…