11 citations · 21 across the 13 of their papers we have counts for
13 papers
Virtual Width Networks
Seed, Baisheng Li, Banggu Wu +115
We introduce Virtual Width Networks (VWN), a framework that delivers the benefits of wider representations without incurring the quadratic cost of increasing the hidden size. VWN d…
VideoMaker: Zero-shot Customized Video Generation with the Inherent Force of Video Diffusion Models
Tao Wu, Yong Zhang, Xiaodong Cun +6
Zero-shot customized video generation has gained significant attention due to its substantial application potential. Existing methods rely on additional models to extract and injec…
CLASH: Complementary Learning with Neural Architecture Search for Gait Recognition
Huanzhang Dou, Pengyi Zhang, Yuhan Zhao +2
Gait recognition, which aims at identifying individuals by their walking patterns, has achieved great success based on silhouette. The binary silhouette sequence encodes the walkin…
GVDIFF: Grounded Text-to-Video Generation with Diffusion Models
Huanzhang Dou, Ruixiang Li, Wei Su +1
In text-to-video (T2V) generation, significant attention has been directed toward its development, yet unifying discrete and continuous grounding conditions in T2V generation remai…
ScanFormer: Referring Expression Comprehension by Iteratively Scanning
Wei Su, Peihan Miao, Huanzhang Dou +1
Referring Expression Comprehension (REC) aims to localize the target objects specified by free-form natural language descriptions in images. While state-of-the-art methods achieve…
SemanticMIM: Marring Masked Image Modeling with Semantics Compression for General Visual Representation
Yike Yuan, Huanzhang Dou, Fengjun Guo +1
This paper represents a neat yet effective framework, named SemanticMIM, to integrate the advantages of masked image modeling (MIM) and contrastive learning (CL) for general visual…
Language Adaptive Weight Generation for Multi-task Visual Grounding
Wei Su, Peihan Miao, Huanzhang Dou +4
Although the impressive performance in visual grounding, the prevailing approaches usually exploit the visual backbone in a passive way, i.e., the visual backbone extracts features…
GaitMPL: Gait Recognition with Memory-Augmented Progressive Learning
Huanzhang Dou, Pengyi Zhang, Yuhan Zhao +3
Gait recognition aims at identifying the pedestrians at a long distance by their biometric gait patterns. It is inherently challenging due to the various covariates and the propert…
Referring Expression Comprehension Using Language Adaptive Inference
Wei Su, Peihan Miao, Huanzhang Dou +2
Different from universal object detection, referring expression comprehension (REC) aims to locate specific objects referred to by natural language expressions. The expression prov…
MetaGait: Learning to Learn an Omni Sample Adaptive Representation for Gait Recognition
Huanzhang Dou, Pengyi Zhang, Wei Su +2
Gait recognition, which aims at identifying individuals by their walking patterns, has recently drawn increasing research attention. However, gait recognition still suffers from th…
GaitGCI: Generative Counterfactual Intervention for Gait Recognition
Huanzhang Dou, Pengyi Zhang, Wei Su +3
Gait is one of the most promising biometrics that aims to identify pedestrians from their walking patterns. However, prevailing methods are susceptible to confounders, resulting in…
VersatileGait: A Large-Scale Synthetic Gait Dataset Towards in-the-Wild Simulation
Pengyi Zhang, Huanzhang Dou, Wenhu Zhang +4
Gait recognition has a rapid development in recent years. However, gait recognition in the wild is not well explored yet. An obvious reason could be ascribed to the lack of diverse…
VersatileGait: A Large-Scale Synthetic Gait Dataset with Fine-GrainedAttributes and Complicated Scenarios
Huanzhang Dou, Wenhu Zhang, Pengyi Zhang +6
With the motivation of practical gait recognition applications, we propose to automatically create a large-scale synthetic gait dataset (called VersatileGait) by a game engine, whi…