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20232026
most citedM2-CLIP: A Multimodal, Multi-task Adapting Framework for Video Action Recognition

4 citations · 7 across the 17 of their papers we have counts for

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Showing 2024Show all

7 papers · 1 filter

cs.CV2024

Visual Object Tracking across Diverse Data Modalities: A Review

Mengmeng Wang, Teli Ma, Shuo Xin +5

Visual Object Tracking (VOT) is an attractive and significant research area in computer vision, which aims to recognize and track specific targets in video sequences where the targ…

cs.CV2024

Low-Biased General Annotated Dataset Generation

Dengyang Jiang, Haoyu Wang, Lei Zhang +5

Pre-training backbone networks on a general annotated dataset (e.g., ImageNet) that comprises numerous manually collected images with category annotations has proven to be indispen…

cs.CV2024

SpotActor: Training-Free Layout-Controlled Consistent Image Generation

Jiahao Wang, Caixia Yan, Weizhan Zhang +6

Text-to-image diffusion models significantly enhance the efficiency of artistic creation with high-fidelity image generation. However, in typical application scenarios like comic b…

cs.CV2024

OneActor: Consistent Character Generation via Cluster-Conditioned Guidance

Jiahao Wang, Caixia Yan, Haonan Lin +5

Text-to-image diffusion models benefit artists with high-quality image generation. Yet their stochastic nature hinders artists from creating consistent images of the same subject.…

cs.CV2024

TryOn-Adapter: Efficient Fine-Grained Clothing Identity Adaptation for High-Fidelity Virtual Try-On

Jiazheng Xing, Chao Xu, Yijie Qian +5

Virtual try-on focuses on adjusting the given clothes to fit a specific person seamlessly while avoiding any distortion of the patterns and textures of the garment. However, the cl…

cs.CV2024

DreamSalon: A Staged Diffusion Framework for Preserving Identity-Context in Editable Face Generation

Haonan Lin, Mengmeng Wang, Yan Chen +6

While large-scale pre-trained text-to-image models can synthesize diverse and high-quality human-centered images, novel challenges arise with a nuanced task of "identity fine editi…

cs.CV2024★ 4 cited

M2-CLIP: A Multimodal, Multi-task Adapting Framework for Video Action Recognition

Mengmeng Wang, Jiazheng Xing, Boyuan Jiang +6

Recently, the rise of large-scale vision-language pretrained models like CLIP, coupled with the technology of Parameter-Efficient FineTuning (PEFT), has captured substantial attrac…