activity
20122023
most citedLearning with Augmented Features for Heterogeneous Domain Adaptation

223 citations · 236 across the 6 of their papers we have counts for

collaborators

10 papers

cs.CV20241 cited

Beyond Viewpoint: Robust 3D Object Recognition under Arbitrary Views through Joint Multi-Part Representation

Linlong Fan, Ye Huang, Yanqi Ge +2

Existing view-based methods excel at recognizing 3D objects from predefined viewpoints, but their exploration of recognition under arbitrary views is limited. This is a challenging…

cs.CV2024

Learning Semantic Latent Directions for Accurate and Controllable Human Motion Prediction

Guowei Xu, Jiale Tao, Wen Li +1

In the realm of stochastic human motion prediction (SHMP), researchers have often turned to generative models like GANS, VAEs and diffusion models. However, most previous approache…

cs.CV20241 cited

Simultaneous Detection and Interaction Reasoning for Object-Centric Action Recognition

Xunsong Li, Pengzhan Sun, Yangcen Liu +2

The interactions between human and objects are important for recognizing object-centric actions. Existing methods usually adopt a two-stage pipeline, where object proposals are fir…

cs.CV2024

SSR: SAM is a Strong Regularizer for domain adaptive semantic segmentation

Yanqi Ge, Ye Huang, Wen Li +1

We introduced SSR, which utilizes SAM (segment-anything) as a strong regularizer during training, to greatly enhance the robustness of the image encoder for handling various domain…

cs.CV2023

Learning Motion Refinement for Unsupervised Face Animation

Jiale Tao, Shuhang Gu, Wen Li +1

Unsupervised face animation aims to generate a human face video based on the appearance of a source image, mimicking the motion from a driving video. Existing methods typically ado…

cs.CV2023

CARD: Semantic Segmentation with Efficient Class-Aware Regularized Decoder

Ye Huang, Di Kang, Liang Chen +5

Semantic segmentation has recently achieved notable advances by exploiting "class-level" contextual information during learning. However, these approaches simply concatenate class-…