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1 code implementation • 7 Oct 2023 • Jiajun Song, Yiqiao Zhong

Given embedding vector $\boldsymbol{h}_{c, t} \in \mathbb{R}^d$ at sequence position $t \le T$ in a sequence (or context) $c \le C$, extracting the mean effects yields the decomposition \[ \boldsymbol{h}_{c, t} = \boldsymbol{\mu} + \mathbf{pos}_t + \mathbf{ctx}_c + \mathbf{resid}_{c, t} \] where $\boldsymbol{\mu}$ is the global mean vector, $\mathbf{pos}_t$ and $\mathbf{ctx}_c$ are the mean vectors across contexts and across positions respectively, and $\mathbf{resid}_{c, t}$ is the residual vector.

1 code implementation • 7 Oct 2023 • Pengfei Zhou, Weiqing Min, Yang Zhang, Jiajun Song, Ying Jin, Shuqiang Jiang

To tackle this, we propose the Semantic Separable Diffusion Synthesizer (SeeDS) framework for Zero-Shot Food Detection (ZSFD).

Ranked #1 on Generalized Zero-Shot Object Detection on MS-COCO

2 code implementations • 9 Feb 2021 • Zhuo Li, Weiqing Min, Jiajun Song, Yaohui Zhu, Liping Kang, Xiaoming Wei, Xiaolin Wei, Shuqiang Jiang

Limited by the definition of AP, such methods consider both negative and positive instances ranking before each positive instance.

Ranked #3 on Vehicle Re-Identification on VehicleID Large

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