13 citations · 28 across the 18 of their papers we have counts for
8 papers · 1 filter
Collaborative Feature-Logits Contrastive Learning for Open-Set Semi-Supervised Object Detection
Xinhao Zhong, Siyu Jiao, Yao Zhao +1
Current Semi-Supervised Object Detection (SSOD) methods enhance detector performance by leveraging large amounts of unlabeled data, assuming that both labeled and unlabeled data sh…
CLIP-GS: Unifying Vision-Language Representation with 3D Gaussian Splatting
Siyu Jiao, Haoye Dong, Yuyang Yin +5
Recent works in 3D multimodal learning have made remarkable progress. However, typically 3D multimodal models are only capable of handling point clouds. Compared to the emerging 3D…
ROSE: Revolutionizing Open-Set Dense Segmentation with Patch-Wise Perceptual Large Multimodal Model
Kunyang Han, Yibo Hu, Mengxue Qu +3
Advances in CLIP and large multimodal models (LMMs) have enabled open-vocabulary and free-text segmentation, yet existing models still require predefined category prompts, limiting…
DreamLCM: Towards High-Quality Text-to-3D Generation via Latent Consistency Model
Yiming Zhong, Xiaolin Zhang, Yao Zhao +1
Recently, the text-to-3D task has developed rapidly due to the appearance of the SDS method. However, the SDS method always generates 3D objects with poor quality due to the over-s…
Collaborative Vision-Text Representation Optimizing for Open-Vocabulary Segmentation
Siyu Jiao, Hongguang Zhu, Jiannan Huang +3
Pre-trained vision-language models, e.g. CLIP, have been increasingly used to address the challenging Open-Vocabulary Segmentation (OVS) task, benefiting from their well-aligned vi…
Frozen CLIP: A Strong Backbone for Weakly Supervised Semantic Segmentation
Bingfeng Zhang, Siyue Yu, Yunchao Wei +2
Weakly supervised semantic segmentation has witnessed great achievements with image-level labels. Several recent approaches use the CLIP model to generate pseudo labels for trainin…
Transferable and Principled Efficiency for Open-Vocabulary Segmentation
Jingxuan Xu, Wuyang Chen, Yao Zhao +1
Recent success of pre-trained foundation vision-language models makes Open-Vocabulary Segmentation (OVS) possible. Despite the promising performance, this approach introduces heavy…
Learning Trimaps via Clicks for Image Matting
Chenyi Zhang, Yihan Hu, Henghui Ding +3
Despite significant advancements in image matting, existing models heavily depend on manually-drawn trimaps for accurate results in natural image scenarios. However, the process of…