8 citations · 27 across the 17 of their papers we have counts for
12 papers · 1 filter
Resolving Representation Ambiguity in Feedforward Novel View Synthesis Transformer via Semantic-Spatial Decoupling
Yihang Wu, Yihang Sun, Shaofeng Zhang +4
Transformer-based models have advanced feedforward novel view synthesis (NVS). Current architectures such as GS-LRM and LVSM mix semantic information (e.g., RGB) and spatial inform…
Dual-Branch Center-Surrounding Contrast: Rethinking Contrastive Learning for 3D Point Clouds
Shaofeng Zhang, Xuanqi Chen, Xiangdong Zhang +2
Most existing self-supervised learning (SSL) approaches for 3D point clouds are dominated by generative methods based on Masked Autoencoders (MAE). However, these generative method…
Spatial Retrieval Augmented Autonomous Driving
Xiaosong Jia, Chenhe Zhang, Yule Jiang +8
Existing autonomous driving systems rely on onboard sensors (cameras, LiDAR, IMU, etc) for environmental perception. However, this paradigm is limited by the drive-time perception…
Towards More Diverse and Challenging Pre-training for Point Cloud Learning: Self-Supervised Cross Reconstruction with Decoupled Views
Xiangdong Zhang, Shaofeng Zhang, Junchi Yan
Point cloud learning, especially in a self-supervised way without manual labels, has gained growing attention in both vision and learning communities due to its potential utility i…
VideoREPA: Learning Physics for Video Generation through Relational Alignment with Foundation Models
Xiangdong Zhang, Jiaqi Liao, Shaofeng Zhang +4
Recent advancements in text-to-video (T2V) diffusion models have enabled high-fidelity and realistic video synthesis. However, current T2V models often struggle to generate physica…
Point2RBox-v2: Rethinking Point-supervised Oriented Object Detection with Spatial Layout Among Instances
Yi Yu, Botao Ren, Peiyuan Zhang +6
With the rapidly increasing demand for oriented object detection (OOD), recent research involving weakly-supervised detectors for learning OOD from point annotations has gained gre…
Exploiting Unlabeled Data with Multiple Expert Teachers for Open Vocabulary Aerial Object Detection and Its Orientation Adaptation
Yan Li, Weiwei Guo, Xue Yang +5
In recent years, aerial object detection has been increasingly pivotal in various earth observation applications. However, current algorithms are limited to detecting a set of pre-…
PCP-MAE: Learning to Predict Centers for Point Masked Autoencoders
Xiangdong Zhang, Shaofeng Zhang, Junchi Yan
Masked autoencoder has been widely explored in point cloud self-supervised learning, whereby the point cloud is generally divided into visible and masked parts. These methods typic…
Continuous-Multiple Image Outpainting in One-Step via Positional Query and A Diffusion-based Approach
Shaofeng Zhang, Jinfa Huang, Qiang Zhou +4
Image outpainting aims to generate the content of an input sub-image beyond its original boundaries. It is an important task in content generation yet remains an open problem for g…
On the Evaluation and Refinement of Vision-Language Instruction Tuning Datasets
Ning Liao, Shaofeng Zhang, Renqiu Xia +3
There is an emerging line of research on multimodal instruction tuning, and a line of benchmarks has been proposed for evaluating these models recently. Instead of evaluating the m…
RegionBLIP: A Unified Multi-modal Pre-training Framework for Holistic and Regional Comprehension
Qiang Zhou, Chaohui Yu, Shaofeng Zhang +3
In this work, we investigate extending the comprehension of Multi-modal Large Language Models (MLLMs) to regional objects. To this end, we propose to extract features corresponding…
Patch-Level Contrasting without Patch Correspondence for Accurate and Dense Contrastive Representation Learning
Shaofeng Zhang, Feng Zhu, Rui Zhao +1
We propose ADCLR: A ccurate and D ense Contrastive Representation Learning, a novel self-supervised learning framework for learning accurate and dense vision representation. To ext…