5 citations · 13 across the 20 of their papers we have counts for
7 papers · 1 filter
Mitigating Semantic Collapse in Partially Relevant Video Retrieval
WonJun Moon, MinSeok Jung, Gilhan Park +4
Partially Relevant Video Retrieval (PRVR) seeks videos where only part of the content matches a text query. Existing methods treat every annotated text-video pair as a positive and…
Scalable GANs with Transformers
Sangeek Hyun, MinKyu Lee, Jae-Pil Heo
Scalability has driven recent advances in generative modeling, yet its principles remain underexplored for adversarial learning. We investigate the scalability of Generative Advers…
Translation of Text Embedding via Delta Vector to Suppress Strongly Entangled Content in Text-to-Image Diffusion Models
Eunseo Koh, Seunghoo Hong, Tae-Young Kim +2
Text-to-Image (T2I) diffusion models have made significant progress in generating diverse high-quality images from textual prompts. However, these models still face challenges in s…
Ambiguity-Restrained Text-Video Representation Learning for Partially Relevant Video Retrieval
CH Cho, WJ Moon, W Jun +2
Partially Relevant Video Retrieval~(PRVR) aims to retrieve a video where a specific segment is relevant to a given text query. Typical training processes of PRVR assume a one-to-on…
Prototypes are Balanced Units for Efficient and Effective Partially Relevant Video Retrieval
WonJun Moon, Cheol-Ho Cho, Woojin Jun +5
In a retrieval system, simultaneously achieving search accuracy and efficiency is inherently challenging. This challenge is particularly pronounced in partially relevant video retr…
Analyzing the Training Dynamics of Image Restoration Transformers: A Revisit to Layer Normalization
MinKyu Lee, Sangeek Hyun, Woojin Jun +3
This work analyzes the training dynamics of Image Restoration (IR) Transformers and uncovers a critical yet overlooked issue: conventional LayerNorm (LN) drives feature magnitudes…
Fine-Tuning Visual Autoregressive Models for Subject-Driven Generation
Jiwoo Chung, Sangeek Hyun, Hyunjun Kim +3
Recent advances in text-to-image generative models have enabled numerous practical applications, including subject-driven generation, which fine-tunes pretrained models to capture…