most citedEfficient Multimodal Large Language Models: A Survey

32 citations · 43 across the 13 of their papers we have counts for

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cs.CV2024

OSV: One Step is Enough for High-Quality Image to Video Generation

Xiaofeng Mao, Zhengkai Jiang, Fu-Yun Wang +5

Video diffusion models have shown great potential in generating high-quality videos, making them an increasingly popular focus. However, their inherent iterative nature leads to su…

cs.CV2024★ 6 cited

MDT-A2G: Exploring Masked Diffusion Transformers for Co-Speech Gesture Generation

Xiaofeng Mao, Zhengkai Jiang, Qilin Wang +7

Recent advancements in the field of Diffusion Transformers have substantially improved the generation of high-quality 2D images, 3D videos, and 3D shapes. However, the effectivenes…

cs.CV2024

NoiseBoost: Alleviating Hallucination with Noise Perturbation for Multimodal Large Language Models

Kai Wu, Boyuan Jiang, Zhengkai Jiang +5

Multimodal large language models (MLLMs) contribute a powerful mechanism to understanding visual information building on large language models. However, MLLMs are notorious for suf…

cs.CV2024★ 1 cited

VividPose: Advancing Stable Video Diffusion for Realistic Human Image Animation

Qilin Wang, Zhengkai Jiang, Chengming Xu +7

Human image animation involves generating a video from a static image by following a specified pose sequence. Current approaches typically adopt a multi-stage pipeline that separat…

cs.CV2024

AdapNet: Adaptive Noise-Based Network for Low-Quality Image Retrieval

Sihe Zhang, Qingdong He, Jinlong Peng +6

Image retrieval aims to identify visually similar images within a database using a given query image. Traditional methods typically employ both global and local features extracted…

cs.CV2024★ 32 cited

Efficient Multimodal Large Language Models: A Survey

Yizhang Jin, Jian Li, Yexin Liu +10

In the past year, Multimodal Large Language Models (MLLMs) have demonstrated remarkable performance in tasks such as visual question answering, visual understanding and reasoning.…

cs.CV2024★ 2 cited

SDSTrack: Self-Distillation Symmetric Adapter Learning for Multi-Modal Visual Object Tracking

Xiaojun Hou, Jiazheng Xing, Yijie Qian +8

Multimodal Visual Object Tracking (VOT) has recently gained significant attention due to its robustness. Early research focused on fully fine-tuning RGB-based trackers, which was i…

cs.CV2024★ 1 cited

Learning Unified Reference Representation for Unsupervised Multi-class Anomaly Detection

Liren He, Zhengkai Jiang, Jinlong Peng +7

In the field of multi-class anomaly detection, reconstruction-based methods derived from single-class anomaly detection face the well-known challenge of "learning shortcuts", where…

cs.CV2024

PointSeg: A Training-Free Paradigm for 3D Scene Segmentation via Foundation Models

Qingdong He, Jinlong Peng, Zhengkai Jiang +2

Recent success of vision foundation models have shown promising performance for the 2D perception tasks. However, it is difficult to train a 3D foundation network directly due to t…

cs.CV2024

DiffuMatting: Synthesizing Arbitrary Objects with Matting-level Annotation

Xiaobin Hu, Xu Peng, Donghao Luo +7

Due to the difficulty and labor-consuming nature of getting highly accurate or matting annotations, there only exists a limited amount of highly accurate labels available to the pu…

cs.CV2024

UniM-OV3D: Uni-Modality Open-Vocabulary 3D Scene Understanding with Fine-Grained Feature Representation

Qingdong He, Jinlong Peng, Zhengkai Jiang +7

3D open-vocabulary scene understanding aims to recognize arbitrary novel categories beyond the base label space. However, existing works not only fail to fully utilize all the avai…

cs.CV2023

Density Matters: Improved Core-set for Active Domain Adaptive Segmentation

Shizhan Liu, Zhengkai Jiang, Yuxi Li +3

Active domain adaptation has emerged as a solution to balance the expensive annotation cost and the performance of trained models in semantic segmentation. However, existing works…