Dong-Jin Kim
11 papers · 2019–2025 · 5 conferences · across top CS/AI conferences
Achievements
Jump to papers ↓+6 more ↓ Show less ↑
π Interdisciplinary Bridge π Academic Marathon (6) π Conference Polyglot (5) π Renaissance Researcher (5) πΊοΈ Taxonomy Completionist (31)
πΊοΈ
Taxonomy Completionist
(31)
π§
Keyword Pioneer
π₯
Unstoppable
(5)
ποΈ
Keyword Collector
(64)
π
Century Club
(11)
π
Trend Setter
Conferences
CVPR (4)
EMNLP (4)
AAAI (1)
ICCV (1)
IJCNLP (1)
Top co-authors
Keywords
image captioning
(5)
semi-supervised learning
(3)
adversarial learning
(2)
generative adversarial network
(2)
video captioning
(1)
multi-task learning
(1)
zero-shot learning
(1)
part-of-speech tagging
(1)
domain adaptation
(1)
visual question answering
(1)
transfer learning
(1)
knowledge distillation
(1)
natural language generation
(1)
multimodal learning
(1)
video understanding
(1)
feature learning
(1)
human-object interaction
(1)
text-to-image generation
(1)
semantic segmentation
(1)
representation learning
(1)
Papers
Sali4Vid: Saliency-Aware Video Reweighting and Adaptive Caption Retrieval for Dense Video Captioning
EMNLP 2025
ViPCap: Retrieval Text-Based Visual Prompts for Lightweight Image Captioning
AAAI 2025
VerbDiff: Text-Only Diffusion Models with Enhanced Interaction Awareness
CVPR 2025
IFCap: Image-like Retrieval and Frequency-based Entity Filtering for Zero-shot Captioning
EMNLP 2024
Preserving Multi-Modal Capabilities of Pre-trained VLMs for Improving Vision-Linguistic Compositionality
EMNLP 2024
Generative Bias for Robust Visual Question Answering
CVPR 2023
DASO: Distribution-Aware Semantics-Oriented Pseudo-Label for Imbalanced Semi-Supervised Learning
CVPR 2022
LabOR: Labeling Only if Required for Domain Adaptive Semantic Segmentation
ICCV 2021
Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach
IJCNLP 2019
Dense Relational Captioning: Triple-Stream Networks for Relationship-Based Captioning
CVPR 2019
Image Captioning with Very Scarce Supervised Data: Adversarial Semi-Supervised Learning Approach
EMNLP 2019