14 citations · 20 across the 13 of their papers we have counts for
10 papers · 1 filter
COMBINER: Composed Image Retrieval Guided by Attribute-based Neighbor Relations
Zixu Li, Yupeng Hu, Zhiwei Chen +3
Composed Image Retrieval (CIR) represents a challenging retrieval task that targets locating specific images through multimodal inputs. Despite recent progress in CIR techniques, p…
Intention-Guided Cognitive Reasoning for Egocentric Long-Term Action Anticipation
Qiaohui Chu, Haoyu Zhang, Meng Liu +3
Long-term action anticipation from egocentric video is critical for applications such as human-computer interaction and assistive technologies, where anticipating user intent enabl…
TextSplat: Text-Guided Semantic Fusion for Generalizable Gaussian Splatting
Zhicong Wu, Hongbin Xu, Gang Xu +6
Recent advancements in Generalizable Gaussian Splatting have enabled robust 3D reconstruction from sparse input views by utilizing feed-forward Gaussian Splatting models, achieving…
Do Vision-Language Transformers Exhibit Visual Commonsense? An Empirical Study of VCR
Zhenyang Li, Yangyang Guo, Kejie Wang +3
Visual Commonsense Reasoning (VCR) calls for explanatory reasoning behind question answering over visual scenes. To achieve this goal, a model is required to provide an acceptable…
Dynamic in Static: Hybrid Visual Correspondence for Self-Supervised Video Object Segmentation
Gensheng Pei, Yazhou Yao, Jianbo Jiao +3
Conventional video object segmentation (VOS) methods usually necessitate a substantial volume of pixel-level annotated video data for fully supervised learning. In this paper, we p…
MaeFuse: Transferring Omni Features with Pretrained Masked Autoencoders for Infrared and Visible Image Fusion via Guided Training
Jiayang Li, Junjun Jiang, Pengwei Liang +2
In this paper, we introduce MaeFuse, a novel autoencoder model designed for Infrared and Visible Image Fusion (IVIF). The existing approaches for image fusion often rely on trainin…
Spatial Structure Constraints for Weakly Supervised Semantic Segmentation
Tao Chen, Yazhou Yao, Xingguo Huang +3
The image-level label has prevailed in weakly supervised semantic segmentation tasks due to its easy availability. Since image-level labels can only indicate the existence or absen…
RTQ: Rethinking Video-language Understanding Based on Image-text Model
Xiao Wang, Yaoyu Li, Tian Gan +3
Recent advancements in video-language understanding have been established on the foundation of image-text models, resulting in promising outcomes due to the shared knowledge betwee…
Uncovering Hidden Connections: Iterative Search and Reasoning for Video-grounded Dialog
Haoyu Zhang, Meng Liu, Yisen Feng +3
In contrast to conventional visual question answering, video-grounded dialog necessitates a profound understanding of both dialog history and video content for accurate response ge…
ELIP: Efficient Discriminative Language-Image Pre-training with Fewer Vision Tokens
Yangyang Guo, Haoyu Zhang, Yongkang Wong +2
Learning a versatile language-image model is computationally prohibitive under a limited computing budget. This paper delves into the \emph{efficient language-image pre-training},…