6 citations · 14 across the 25 of their papers we have counts for
12 papers · 1 filter
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…
SocialGPT: Prompting LLMs for Social Relation Reasoning via Greedy Segment Optimization
Wanhua Li, Zibin Meng, Jiawei Zhou +3
Social relation reasoning aims to identify relation categories such as friends, spouses, and colleagues from images. While current methods adopt the paradigm of training a dedicate…
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…
Tree of Attributes Prompt Learning for Vision-Language Models
Tong Ding, Wanhua Li, Zhongqi Miao +1
Prompt learning has proven effective in adapting vision language models for downstream tasks. However, existing methods usually append learnable prompt tokens solely with the categ…
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,…
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…
Aligning Sight and Sound: Advanced Sound Source Localization Through Audio-Visual Alignment
Arda Senocak, Hyeonggon Ryu, Junsik Kim +3
Recent studies on learning-based sound source localization have mainly focused on the localization performance perspective. However, prior work and existing benchmarks overlook a c…
Joint-Task Regularization for Partially Labeled Multi-Task Learning
Kento Nishi, Junsik Kim, Wanhua Li +1
Multi-task learning has become increasingly popular in the machine learning field, but its practicality is hindered by the need for large, labeled datasets. Most multi-task learnin…
Frenet-Serret Frame-based Decomposition for Part Segmentation of 3D Curvilinear Structures
Leslie Gu, Jason Ken Adhinarta, Mikhail Bessmeltsev +7
Accurately segmenting 3D curvilinear structures in medical imaging remains challenging due to their complex geometry and the scarcity of diverse, large-scale datasets for algorithm…
-Tuning: Efficient Image-to-Video Transfer Learning for Video Temporal Grounding
Ye Liu, Jixuan He, Wanhua Li +4
Video temporal grounding (VTG) is a fine-grained video understanding problem that aims to ground relevant clips in untrimmed videos given natural language queries. Most existing VT…
Deep Rib Fracture Instance Segmentation and Classification from CT on the RibFrac Challenge
Jiancheng Yang, Rui Shi, Liang Jin +22
Rib fractures are a common and potentially severe injury that can be challenging and labor-intensive to detect in CT scans. While there have been efforts to address this field, the…
TriSAM: Tri-Plane SAM for zero-shot cortical blood vessel segmentation in VEM images
Jia Wan, Wanhua Li, Jason Ken Adhinarta +6
While imaging techniques at macro and mesoscales have garnered substantial attention and resources, microscale Volume Electron Microscopy (vEM) imaging, capable of revealing intric…