activity
20202023
most citedPrediction Calibration for Generalized Few-shot Semantic Segmentation

29 citations · 154 across the 36 of their papers we have counts for

collaborators
Showing 2022Show all

19 papers · 1 filter

cs.CV2022★ 3 cited

Single Stage Multi-Pose Virtual Try-On

Sen He, Yi-Zhe Song, Tao Xiang

Multi-pose virtual try-on (MPVTON) aims to fit a target garment onto a person at a target pose. Compared to traditional virtual try-on (VTON) that fits the garment but keeps the po…

cs.CV2022

Post-Processing Temporal Action Detection

Sauradip Nag, Xiatian Zhu, Yi-Zhe Song +1

Existing Temporal Action Detection (TAD) methods typically take a pre-processing step in converting an input varying-length video into a fixed-length snippet representation sequenc…

cs.CV2022★ 1 cited

Multi-Modal Few-Shot Temporal Action Detection

Sauradip Nag, Mengmeng Xu, Xiatian Zhu +4

Few-shot (FS) and zero-shot (ZS) learning are two different approaches for scaling temporal action detection (TAD) to new classes. The former adapts a pretrained vision model to a…

cs.CV2022

Where is my Wallet? Modeling Object Proposal Sets for Egocentric Visual Query Localization

Mengmeng Xu, Yanghao Li, Cheng-Yang Fu +3

This paper deals with the problem of localizing objects in image and video datasets from visual exemplars. In particular, we focus on the challenging problem of egocentric visual q…

cs.CV2022★ 2 cited

FaD-VLP: Fashion Vision-and-Language Pre-training towards Unified Retrieval and Captioning

Suvir Mirchandani, Licheng Yu, Mengjiao Wang +4

Multimodal tasks in the fashion domain have significant potential for e-commerce, but involve challenging vision-and-language learning problems - e.g., retrieving a fashion item gi…

cs.CV2022

Learning to Augment via Implicit Differentiation for Domain Generalization

Tingwei Wang, Da Li, Kaiyang Zhou +2

Machine learning models are intrinsically vulnerable to domain shift between training and testing data, resulting in poor performance in novel domains. Domain generalization (DG) a…

cs.CV2022★ 29 cited

Prediction Calibration for Generalized Few-shot Semantic Segmentation

Zhihe Lu, Sen He, Da Li +2

Generalized Few-shot Semantic Segmentation (GFSS) aims to segment each image pixel into either base classes with abundant training examples or novel classes with only a handful of…

cs.CV2022★ 2 cited

Robust Target Training for Multi-Source Domain Adaptation

Zhongying Deng, Da Li, Yi-Zhe Song +1

Given multiple labeled source domains and a single target domain, most existing multi-source domain adaptation (MSDA) models are trained on data from all domains jointly in one ste…

cs.CV2022

Structure-Aware 3D VR Sketch to 3D Shape Retrieval

Ling Luo, Yulia Gryaditskaya, Tao Xiang +1

We study the practical task of fine-grained 3D-VR-sketch-based 3D shape retrieval. This task is of particular interest as 2D sketches were shown to be effective queries for 2D imag…

cs.CV2022★ 3 cited

Proposal-Free Temporal Action Detection via Global Segmentation Mask Learning

Sauradip Nag, Xiatian Zhu, Yi-Zhe Song +1

Existing temporal action detection (TAD) methods rely on generating an overwhelmingly large number of proposals per video. This leads to complex model designs due to proposal gener…

cs.CV2022★ 4 cited

Adaptive Fine-Grained Sketch-Based Image Retrieval

Ayan Kumar Bhunia, Aneeshan Sain, Parth Shah +4

The recent focus on Fine-Grained Sketch-Based Image Retrieval (FG-SBIR) has shifted towards generalising a model to new categories without any training data from them. In real-worl…

cs.CV2022★ 4 cited

Negative Frames Matter in Egocentric Visual Query 2D Localization

Mengmeng Xu, Cheng-Yang Fu, Yanghao Li +3

The recently released Ego4D dataset and benchmark significantly scales and diversifies the first-person visual perception data. In Ego4D, the Visual Queries 2D Localization task ai…

cs.CV2022★ 4 cited

Zero-Shot Temporal Action Detection via Vision-Language Prompting

Sauradip Nag, Xiatian Zhu, Yi-Zhe Song +1

Existing temporal action detection (TAD) methods rely on large training data including segment-level annotations, limited to recognizing previously seen classes alone during infere…

cs.CV2022★ 4 cited

FashionViL: Fashion-Focused Vision-and-Language Representation Learning

Xiao Han, Licheng Yu, Xiatian Zhu +3

Large-scale Vision-and-Language (V+L) pre-training for representation learning has proven to be effective in boosting various downstream V+L tasks. However, when it comes to the fa…

cs.CV2022★ 1 cited

Semi-Supervised Temporal Action Detection with Proposal-Free Masking

Sauradip Nag, Xiatian Zhu, Yi-Zhe Song +1

Existing temporal action detection (TAD) methods rely on a large number of training data with segment-level annotations. Collecting and annotating such a training set is thus highl…

cs.CV2022★ 18 cited

Vision Transformers: From Semantic Segmentation to Dense Prediction

Li Zhang, Jiachen Lu, Sixiao Zheng +6

The emergence of vision transformers (ViTs) in image classification has shifted the methodologies for visual representation learning. In particular, ViTs learn visual representatio…

cs.CV2022★ 11 cited

Softmax-free Linear Transformers

Jiachen Lu, Junge Zhang, Xiatian Zhu +3

Vision transformers (ViTs) have pushed the state-of-the-art for visual perception tasks. The self-attention mechanism underpinning the strength of ViTs has a quadratic complexity i…

cs.CV2022★ 2 cited

UIGR: Unified Interactive Garment Retrieval

Xiao Han, Sen He, Li Zhang +2

Interactive garment retrieval (IGR) aims to retrieve a target garment image based on a reference garment image along with user feedback on what to change on the reference garment.…

cs.CV2022★ 3 cited

SceneTrilogy: On Human Scene-Sketch and its Complementarity with Photo and Text

Pinaki Nath Chowdhury, Ayan Kumar Bhunia, Aneeshan Sain +3

In this paper, we extend scene understanding to include that of human sketch. The result is a complete trilogy of scene representation from three diverse and complementary modaliti…