3 citations · 5 across the 9 of their papers we have counts for
9 papers
Text-guided Controllable Diffusion for Realistic Camouflage Images Generation
Yuhang Qian, Haiyan Chen, Wentong Li +2
Camouflage Images Generation (CIG) is an emerging research area that focuses on synthesizing images in which objects are harmoniously blended and exhibit high visual consistency wi…
APGNet: Adaptive Prior-Guided for Underwater Camouflaged Object Detection
Xinxin Huang, Han Sun, Junmin Cai +2
Detecting camouflaged objects in underwater environments is crucial for marine ecological research and resource exploration. However, existing methods face two key challenges: unde…
SLENet: A Guidance-Enhanced Network for Underwater Camouflaged Object Detection
Xinxin Huang, Han Sun, Ningzhong Liu +2
Underwater Camouflaged Object Detection (UCOD) aims to identify objects that blend seamlessly into underwater environments. This task is critically important to marine ecology. How…
SliceSemOcc: Vertical Slice Based Multimodal 3D Semantic Occupancy Representation
Han Huang, Han Sun, Ningzhong Liu +2
Driven by autonomous driving's demands for precise 3D perception, 3D semantic occupancy prediction has become a pivotal research topic. Unlike bird's-eye-view (BEV) methods, which…
DCFS: Continual Test-Time Adaptation via Dual Consistency of Feature and Sample
Wenting Yin, Han Sun, Xinru Meng +2
Continual test-time adaptation aims to continuously adapt a pre-trained model to a stream of target domain data without accessing source data. Without access to source domain data,…
Energy-Based Pseudo-Label Refining for Source-free Domain Adaptation
Xinru Meng, Han Sun, Jiamei Liu +2
Source-free domain adaptation (SFDA), which involves adapting models without access to source data, is both demanding and challenging. Existing SFDA techniques typically rely on ps…
SPARNet: Continual Test-Time Adaptation via Sample Partitioning Strategy and Anti-Forgetting Regularization
Xinru Meng, Han Sun, Jiamei Liu +2
Test-time Adaptation (TTA) aims to improve model performance when the model encounters domain changes after deployment. The standard TTA mainly considers the case where the target…
B2Net: Camouflaged Object Detection via Boundary Aware and Boundary Fusion
Junmin Cai, Han Sun, Ningzhong Liu
Camouflaged object detection (COD) aims to identify objects in images that are well hidden in the environment due to their high similarity to the background in terms of texture and…
DecoratingFusion: A LiDAR-Camera Fusion Network with the Combination of Point-level and Feature-level Fusion
Zixuan Yin, Han Sun, Ningzhong Liu +2
Lidars and cameras play essential roles in autonomous driving, offering complementary information for 3D detection. The state-of-the-art fusion methods integrate them at the featur…