most citedDiverse Human Motion Prediction Guided by Multi-Level Spatial-Temporal Anchors

43 citations · 70 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2024

Floating No More: Object-Ground Reconstruction from a Single Image

Yunze Man, Yichen Sheng, Jianming Zhang +2

Recent advancements in 3D object reconstruction from single images have primarily focused on improving the accuracy of object shapes. Yet, these techniques often fail to accurately…

cs.CV20244 cited

HASSOD: Hierarchical Adaptive Self-Supervised Object Detection

Shengcao Cao, Dhiraj Joshi, Liang-Yan Gui +1

The human visual perception system demonstrates exceptional capabilities in learning without explicit supervision and understanding the part-to-whole composition of objects. Drawin…

cs.CV202312 cited

Aligning Large Multimodal Models with Factually Augmented RLHF

Zhiqing Sun, Sheng Shen, Shengcao Cao +9

Large Multimodal Models (LMM) are built across modalities and the misalignment between two modalities can result in "hallucination", generating textual outputs that are not grounde…

cs.CV20232 cited

InterDiff: Generating 3D Human-Object Interactions with Physics-Informed Diffusion

Sirui Xu, Zhengyuan Li, Yu-Xiong Wang +1

This paper addresses a novel task of anticipating 3D human-object interactions (HOIs). Most existing research on HOI synthesis lacks comprehensive whole-body interactions with dyna…

cs.CV20233 cited

Learning Lightweight Object Detectors via Multi-Teacher Progressive Distillation

Shengcao Cao, Mengtian Li, James Hays +3

Resource-constrained perception systems such as edge computing and vision-for-robotics require vision models to be both accurate and lightweight in computation and memory usage. Wh…

cs.CV20233 cited

Stochastic Multi-Person 3D Motion Forecasting

Sirui Xu, Yu-Xiong Wang, Liang-Yan Gui

This paper aims to deal with the ignored real-world complexities in prior work on human motion forecasting, emphasizing the social properties of multi-person motion, the diversity…