5 citations · 21 across the 11 of their papers we have counts for
12 papers
Towards Effective Collaborative Learning in Long-Tailed Recognition
Zhengzhuo Xu, Zenghao Chai, Chengyin Xu +2
Real-world data usually suffers from severe class imbalance and long-tailed distributions, where minority classes are significantly underrepresented compared to the majority ones.…
HiFace: High-Fidelity 3D Face Reconstruction by Learning Static and Dynamic Details
Zenghao Chai, Tianke Zhang, Tianyu He +7
3D Morphable Models (3DMMs) demonstrate great potential for reconstructing faithful and animatable 3D facial surfaces from a single image. The facial surface is influenced by the c…
SEAM: Searching Transferable Mixed-Precision Quantization Policy through Large Margin Regularization
Chen Tang, Kai Ouyang, Zenghao Chai +4
Mixed-precision quantization (MPQ) suffers from the time-consuming process of searching the optimal bit-width allocation i.e., the policy) for each layer, especially when using lar…
ERA-Solver: Error-Robust Adams Solver for Fast Sampling of Diffusion Probabilistic Models
Shengming Li, Luping Liu, Runnan Li +1
Though denoising diffusion probabilistic models (DDPMs) have achieved remarkable generation results, the low sampling efficiency of DDPMs still limits further applications. Since D…
Learning Imbalanced Data with Vision Transformers
Zhengzhuo Xu, Ruikang Liu, Shuo Yang +2
The real-world data tends to be heavily imbalanced and severely skew the data-driven deep neural networks, which makes Long-Tailed Recognition (LTR) a massive challenging task. Exi…
HyP Loss: Beyond Hypersphere Metric Space for Multi-label Image Retrieval
Chengyin Xu, Zenghao Chai, Zhengzhuo Xu +3
Image retrieval has become an increasingly appealing technique with broad multimedia application prospects, where deep hashing serves as the dominant branch towards low storage and…
REALY: Rethinking the Evaluation of 3D Face Reconstruction
Zenghao Chai, Haoxian Zhang, Jing Ren +5
The evaluation of 3D face reconstruction results typically relies on a rigid shape alignment between the estimated 3D model and the ground-truth scan. We observe that aligning two…
HHF: Hashing-guided Hinge Function for Deep Hashing Retrieval
Chengyin Xu, Zenghao Chai, Zhengzhuo Xu +4
Deep hashing has shown promising performance in large-scale image retrieval. However, latent codes extracted by Deep Neural Networks (DNNs) will inevitably lose semantic informatio…
Semantic-Sparse Colorization Network for Deep Exemplar-based Colorization
Yunpeng Bai, Chao Dong, Zenghao Chai +3
Exemplar-based colorization approaches rely on reference image to provide plausible colors for target gray-scale image. The key and difficulty of exemplar-based colorization is to…
Towards Calibrated Model for Long-Tailed Visual Recognition from Prior Perspective
Zhengzhuo Xu, Zenghao Chai, Chun Yuan
Real-world data universally confronts a severe class-imbalance problem and exhibits a long-tailed distribution, i.e., most labels are associated with limited instances. The naïve m…
MoDeRNN: Towards Fine-grained Motion Details for Spatiotemporal Predictive Learning
Zenghao Chai, Zhengzhuo Xu, Chun Yuan
Spatiotemporal predictive learning (ST-PL) aims at predicting the subsequent frames via limited observed sequences, and it has broad applications in the real world. However, learni…
CMS-LSTM: Context Embedding and Multi-Scale Spatiotemporal Expression LSTM for Predictive Learning
Zenghao Chai, Zhengzhuo Xu, Yunpeng Bai +2
Spatiotemporal predictive learning (ST-PL) is a hotspot with numerous applications, such as object movement and meteorological prediction. It aims at predicting the subsequent fram…