most citedDetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks

2 citations · 2 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2026

Loki: Representation over Architecture for Diffusion-Based Portrait Animation

Pouyan Navard, Sernam Lim

Portrait animation transfers a driver clip's facial expression and head pose onto a single reference image while preserving the reference's identity. State-of-the-art diffusion sys…

cs.CL2026

Density-aware Soft Context Compression with Semi-Dynamic Compression Ratio

Yijiong Yu, Shuai Yuan, Jie Zheng +2

Soft context compression reduces the computational workload of processing long contexts in LLMs by encoding long context into a smaller number of latent tokens. However, existing f…

cs.CV2024

DLaVA: Document Language and Vision Assistant for Answer Localization with Enhanced Interpretability and Trustworthiness

Ahmad Mohammadshirazi, Pinaki Prasad Guha Neogi, Ser-Nam Lim +1

Document Visual Question Answering (VQA) demands robust integration of text detection, recognition, and spatial reasoning to interpret complex document layouts. In this work, we in…

cs.CV2024

Frequency-Guided Masking for Enhanced Vision Self-Supervised Learning

Amin Karimi Monsefi, Mengxi Zhou, Nastaran Karimi Monsefi +3

We present a novel frequency-based Self-Supervised Learning (SSL) approach that significantly enhances its efficacy for pre-training. Prior work in this direction masks out pre-def…

cs.CV2024★ 2 cited

DetailCLIP: Detail-Oriented CLIP for Fine-Grained Tasks

Amin Karimi Monsefi, Kishore Prakash Sailaja, Ali Alilooee +2

In this paper, we introduce DetailCLIP: A Detail-Oriented CLIP to address the limitations of contrastive learning-based vision-language models, particularly CLIP, in handling detai…