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Found 14 papers, 4 papers with code
GaitSTR: Gait Recognition with Sequential Two-stream Refinement
We demonstrate that with refined skeletons, the performance of the gait recognition model can achieve further improvement on public gait recognition datasets compared with state-of-the-art methods without extra annotations.
Large Language Models are Good Prompt Learners for Low-Shot Image Classification
Thus, we propose LLaMP, Large Language Models as Prompt learners, that produces adaptive prompts for the CLIP text encoder, establishing it as the connecting bridge.
ShARc: Shape and Appearance Recognition for Person Identification In-the-wild
PSE encodes the body shape via binarized silhouettes, skeleton motions, and 3-D body shape, while AAE provides two levels of temporal appearance feature aggregation: attention-based feature aggregation and averaging aggregation.
CAILA: Concept-Aware Intra-Layer Adapters for Compositional Zero-Shot Learning
In this paper, we study the problem of Compositional Zero-Shot Learning (CZSL), which is to recognize novel attribute-object combinations with pre-existing concepts.
Adversarial Demonstration Attacks on Large Language Models
We propose a novel attack method named advICL, which aims to manipulate only the demonstration without changing the input to mislead the models.
GaitRef: Gait Recognition with Refined Sequential Skeletons
Two common modalities used for representing the walking sequence of a person are silhouettes and joint skeletons.
Ranked #3 on
Multiview Gait Recognition
on CASIA-B
CAT-NeRF: Constancy-Aware Tx$^2$Former for Dynamic Body Modeling
This paper addresses the problem of human rendering in the video with temporal appearance constancy.
MoMo: A shared encoder Model for text, image and multi-Modal representations
The results on downstream text-only, image-only and multimodal tasks show that our model is competitive with several strong models while using fewer parameters and lesser pre-training data.
Gait Recognition Using 3-D Human Body Shape Inference
Gait recognition, which identifies individuals based on their walking patterns, is an important biometric technique since it can be observed from a distance and does not require the subject's cooperation.
PatchZero: Defending against Adversarial Patch Attacks by Detecting and Zeroing the Patch
Despite the diversity in attack patterns, adversarial patches tend to be highly textured and different in appearance from natural images.
FashionVLP: Vision Language Transformer for Fashion Retrieval With Feedback
Fashion image retrieval based on a query pair of reference image and natural language feedback is a challenging task that requires models to assess fashion related information from visual and textual modalities simultaneously.
Weakly Supervised Scene Graph Grounding
Recent researches have achieved substantial advances in learning structured representations from images.
Utilizing Every Image Object for Semi-supervised Phrase Grounding
The annotated language queries available during training are limited, which also limits the variations of language combinations that a model can see during training.
