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researcher

Bo Dai

95 papers hereh-index 5012.8k citations152 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author8
  • middle author60
  • last author25

Across the 93 of 95 papers where every author was matched, so the position is known.

fields
  • cs.CV58
  • cs.LG22
  • cs.AI3
  • cs.CL3
  • math.OC2
  • stat.ML2
same name
  • Bo Dai — 44 papers, h 36
  • Bo Dai — 19 papers, h 9
  • Bo Dai — 13 papers, h 6
  • Bo Dai — 12 papers, h 4
  • Bo Dai — 9 papers, h 2
  • Bo Dai — 9 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172024
most citedTowards Diverse and Natural Image Descriptions via a Conditional GAN

106 citations · 1k across the 95 of their papers we have counts for

collaborators
Showing 2018Show all

4 papers · 1 filter

cs.CV2018★ 34 cited

A Neural Compositional Paradigm for Image Captioning

Bo Dai, Sanja Fidler, Dahua Lin

Mainstream captioning models often follow a sequential structure to generate captions, leading to issues such as introduction of irrelevant semantics, lack of diversity in the gene…

cs.LG2018★ 4 cited

Neural Network Encapsulation

Hongyang Li, Xiaoyang Guo, Bo Dai +2

A capsule is a collection of neurons which represents different variants of a pattern in the network. The routing scheme ensures only certain capsules which resemble lower counterp…

cs.CV2018★ 7 cited

Move Forward and Tell: A Progressive Generator of Video Descriptions

Yilei Xiong, Bo Dai, Dahua Lin

We present an efficient framework that can generate a coherent paragraph to describe a given video. Previous works on video captioning usually focus on video clips. They typically…

cs.CV2018

Rethinking the Form of Latent States in Image Captioning

Bo Dai, Deming Ye, Dahua Lin

RNNs and their variants have been widely adopted for image captioning. In RNNs, the production of a caption is driven by a sequence of latent states. Existing captioning models usu…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.