32 citations · 87 across the 8 of their papers we have counts for
9 papers
Next Patch Prediction for Autoregressive Visual Generation
Yatian Pang, Peng Jin, Shuo Yang +8
Autoregressive models, built based on the Next Token Prediction (NTP) paradigm, show great potential in developing a unified framework that integrates both language and vision task…
DreamDance: Animating Human Images by Enriching 3D Geometry Cues from 2D Poses
Yatian Pang, Bin Zhu, Bin Lin +5
In this work, we present DreamDance, a novel method for animating human images using only skeleton pose sequences as conditional inputs. Existing approaches struggle with generatin…
Envision3D: One Image to 3D with Anchor Views Interpolation
Yatian Pang, Tanghui Jia, Yujun Shi +6
We present Envision3D, a novel method for efficiently generating high-quality 3D content from a single image. Recent methods that extract 3D content from multi-view images generate…
Masked Autoencoders for Point Cloud Self-supervised Learning
Yatian Pang, Wenxiao Wang, Francis E. H. Tay +3
As a promising scheme of self-supervised learning, masked autoencoding has significantly advanced natural language processing and computer vision. Inspired by this, we propose a ne…
Tokens-to-Token ViT: Training Vision Transformers from Scratch on ImageNet
Li Yuan, Yunpeng Chen, Tao Wang +6
Transformers, which are popular for language modeling, have been explored for solving vision tasks recently, e.g., the Vision Transformer (ViT) for image classification. The ViT mo…
Fooling the primate brain with minimal, targeted image manipulation
Li Yuan, Will Xiao, Giorgia Dellaferrera +4
Artificial neural networks (ANNs) are considered the current best models of biological vision. ANNs are the best predictors of neural activity in the ventral stream; moreover, rece…
Revisiting Knowledge Distillation via Label Smoothing Regularization
Li Yuan, Francis E. H. Tay, Guilin Li +2
Knowledge Distillation (KD) aims to distill the knowledge of a cumbersome teacher model into a lightweight student model. Its success is generally attributed to the privileged info…
Central Similarity Quantization for Efficient Image and Video Retrieval
Li Yuan, Tao Wang, Xiaopeng Zhang +4
Existing data-dependent hashing methods usually learn hash functions from pairwise or triplet data relationships, which only capture the data similarity locally, and often suffer f…
Cycle-SUM: Cycle-consistent Adversarial LSTM Networks for Unsupervised Video Summarization
Li Yuan, Francis EH Tay, Ping Li +2
In this paper, we present a novel unsupervised video summarization model that requires no manual annotation. The proposed model termed Cycle-SUM adopts a new cycle-consistent adver…