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Found 13 papers, 7 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.
The Efficiency Spectrum of Large Language Models: An Algorithmic Survey
The rapid growth of Large Language Models (LLMs) has been a driving force in transforming various domains, reshaping the artificial general intelligence landscape.
CaesarNeRF: Calibrated Semantic Representation for Few-shot Generalizable Neural Rendering
CaesarNeRF explicitly models pose differences of reference views to combine scene-level semantic representations, providing a calibrated holistic understanding.
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.
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.
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.
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.
CPARR: Category-based Proposal Analysis for Referring Relationships
The task of referring relationships is to localize subject and object entities in an image satisfying a relationship query, which is given in the form of \texttt{<subject, predicate, object>}.
Curriculum DeepSDF
When learning to sketch, beginners start with simple and flexible shapes, and then gradually strive for more complex and accurate ones in the subsequent training sessions.
Pick-and-Learn: Automatic Quality Evaluation for Noisy-Labeled Image Segmentation
We propose a solution for network automatically evaluating the relative quality of the labels in the training set and using good ones to tune the network parameters.
