400 citations · 483 across the 5 of their papers we have counts for
5 papers
Why Are Conditional Generative Models Better Than Unconditional Ones?
Fan Bao, Chongxuan Li, Jiacheng Sun +1
Extensive empirical evidence demonstrates that conditional generative models are easier to train and perform better than unconditional ones by exploiting the labels of data. So do…
DQ-DETR: Dual Query Detection Transformer for Phrase Extraction and Grounding
Shilong Liu, Yaoyuan Liang, Feng Li +5
In this paper, we study the problem of visual grounding by considering both phrase extraction and grounding (PEG). In contrast to the previous phrase-known-at-test setting, PEG req…
Improving transferability of 3D adversarial attacks with scale and shear transformations
Jinali Zhang, Yinpeng Dong, Jun Zhu +3
Previous work has shown that 3D point cloud classifiers can be vulnerable to adversarial examples. However, most of the existing methods are aimed at white-box attacks, where the p…
DAB-DETR: Dynamic Anchor Boxes are Better Queries for DETR
Shilong Liu, Feng Li, Hao Zhang +5
We present in this paper a novel query formulation using dynamic anchor boxes for DETR (DEtection TRansformer) and offer a deeper understanding of the role of queries in DETR. This…
Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models
Fan Bao, Chongxuan Li, Jun Zhu +1
Diffusion probabilistic models (DPMs) represent a class of powerful generative models. Despite their success, the inference of DPMs is expensive since it generally needs to iterate…