2 citations · 2 across the 9 of their papers we have counts for
10 papers
Efficient Learned Image Compression without Entropy Coding
Hao Cao, Wenqi Guo, Zhijin Qin +1
Entropy coding is widely used in typical learned image compression (LIC) that converts latents into a compact bitstream. However, entropy coding is typically sequential and becomes…
Text-Guided Visual Representation Learning for Robust Multimodal E-Commerce Recommendation
Yufei Guo, Jing Ma, Tianlu Zhang +5
Multimodal item embeddings are crucial for e-commerce item-to-item (I2I) retrieval, yet real-world product images often contain promotional overlays and background clutter that inj…
Mostly Text, Smart Visuals: Asymmetric Text-Visual Pruning for Large Vision-Language Models
Sijie Li, Biao Qian, Jungong Han
Network pruning is an effective technique for enabling lightweight Large Vision-Language Models (LVLMs), which primarily incorporates both weights and activations into the importan…
Interpretable Few-Shot Image Classification via Prototypical Concept-Guided Mixture of LoRA Experts
Zhong Ji, Rongshuai Wei, Jingren Liu +2
Self-Explainable Models (SEMs) rely on Prototypical Concept Learning (PCL) to enable their visual recognition processes more interpretable, but they often struggle in data-scarce s…
iEBAKER: Improved Remote Sensing Image-Text Retrieval Framework via Eliminate Before Align and Keyword Explicit Reasoning
Yan Zhang, Zhong Ji, Changxu Meng +2
Recent studies focus on the Remote Sensing Image-Text Retrieval (RSITR), which aims at searching for the corresponding targets based on the given query. Among these efforts, the ap…
Underlying Semantic Diffusion for Effective and Efficient In-Context Learning
Zhong Ji, Weilong Cao, Yan Zhang +3
Diffusion models has emerged as a powerful framework for tasks like image controllable generation and dense prediction. However, existing models often struggle to capture underlyin…
Multi-Stage Knowledge Integration of Vision-Language Models for Continual Learning
Hongsheng Zhang, Zhong Ji, Jingren Liu +2
Vision Language Models (VLMs), pre-trained on large-scale image-text datasets, enable zero-shot predictions for unseen data but may underperform on specific unseen tasks. Continual…
Parameter-Efficient Fine-Tuning for Continual Learning: A Neural Tangent Kernel Perspective
Jingren Liu, Zhong Ji, YunLong Yu +4
Parameter-efficient fine-tuning for continual learning (PEFT-CL) has shown promise in adapting pre-trained models to sequential tasks while mitigating catastrophic forgetting probl…
VIP: Versatile Image Outpainting Empowered by Multimodal Large Language Model
Jinze Yang, Haoran Wang, Zining Zhu +3
In this paper, we focus on resolving the problem of image outpainting, which aims to extrapolate the surrounding parts given the center contents of an image. Although recent works…
Raformer: Redundancy-Aware Transformer for Video Wire Inpainting
Zhong Ji, Yimu Su, Yan Zhang +3
Video Wire Inpainting (VWI) is a prominent application in video inpainting, aimed at flawlessly removing wires in films or TV series, offering significant time and labor savings co…