25 citations · 73 across the 11 of their papers we have counts for
10 papers · 1 filter
Ctrl123: Consistent Novel View Synthesis via Closed-Loop Transcription
Hongxiang Zhao, Xili Dai, Jianan Wang +5
Large image diffusion models have demonstrated zero-shot capability in novel view synthesis (NVS). However, existing diffusion-based NVS methods struggle to generate novel views th…
Image Clustering via the Principle of Rate Reduction in the Age of Pretrained Models
Tianzhe Chu, Shengbang Tong, Tianjiao Ding +4
The advent of large pre-trained models has brought about a paradigm shift in both visual representation learning and natural language processing. However, clustering unlabeled imag…
Closed-Loop Transcription via Convolutional Sparse Coding
Xili Dai, Ke Chen, Shengbang Tong +9
Autoencoding has achieved great empirical success as a framework for learning generative models for natural images. Autoencoders often use generic deep networks as the encoder or d…
Unsupervised Learning of Structured Representations via Closed-Loop Transcription
Shengbang Tong, Xili Dai, Yubei Chen +5
This paper proposes an unsupervised method for learning a unified representation that serves both discriminative and generative purposes. While most existing unsupervised learning…
Revisiting Sparse Convolutional Model for Visual Recognition
Xili Dai, Mingyang Li, Pengyuan Zhai +6
Despite strong empirical performance for image classification, deep neural networks are often regarded as ``black boxes'' and they are difficult to interpret. On the other hand, sp…
Incremental Learning of Structured Memory via Closed-Loop Transcription
Shengbang Tong, Xili Dai, Ziyang Wu +3
This work proposes a minimal computational model for learning structured memories of multiple object classes in an incremental setting. Our approach is based on establishing a clos…
Closed-Loop Data Transcription to an LDR via Minimaxing Rate Reduction
Xili Dai, Shengbang Tong, Mingyang Li +8
This work proposes a new computational framework for learning a structured generative model for real-world datasets. In particular, we propose to learn a closed-loop transcription…
Fully Convolutional Line Parsing
Xili Dai, Haigang Gong, Shuai Wu +2
We present a one-stage Fully Convolutional Line Parsing network (F-Clip) that detects line segments from images. The proposed network is very simple and flexible with variations th…
Learning to Reconstruct 3D Non-Cuboid Room Layout from a Single RGB Image
Cheng Yang, Jia Zheng, Xili Dai +3
Single-image room layout reconstruction aims to reconstruct the enclosed 3D structure of a room from a single image. Most previous work relies on the cuboid-shape prior. This paper…
HoliCity: A City-Scale Data Platform for Learning Holistic 3D Structures
Yichao Zhou, Jingwei Huang, Xili Dai +4
We present HoliCity, a city-scale 3D dataset with rich structural information. Currently, this dataset has 6,300 real-world panoramas of resolution that are acc…