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20202026
most citedImproving Wildlife Out-of-Distribution Detection: Africas Big Five

1 citations · 1 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2026

Visual-Prompt Guided Wildlife Instance-Level Recognition

Mufhumudzi Muthivhi, Jiahao Huo, Terence van Zyl +1

Fine-grained wildlife re-identification remains a challenging area in research. Current state-of-the-art approaches apply a detection and re-identification pipeline. We propose a o…

cs.CV2026

Multi-Object Tracking Consistently Improves Wildlife Inference

Mufhumudzi Muthivhi, Jiahao Huo, Fredrik Gustafsson +1

Camera traps have become a common tool for wildlife monitoring efforts in ecological research and biodiversity conservation. Wildlife classification models have benefited from the…

cs.CV2025

Nearest-Class Mean and Logits Agreement for Wildlife Open-Set Recognition

Jiahao Huo, Mufhumudzi Muthivhi, Terence L. van Zyl +1

Current state-of-the-art Wildlife classification models are trained under the closed world setting. When exposed to unknown classes, they remain overconfident in their predictions.…

cs.CV2025★ 1 cited

Improving Wildlife Out-of-Distribution Detection: Africas Big Five

Mufhumudzi Muthivhi, Jiahao Huo, Fredrik Gustafsson +1

Mitigating human-wildlife conflict seeks to resolve unwanted encounters between these parties. Computer Vision provides a solution to identifying individuals that might escalate in…

cs.LG2021

Incremental Class Learning using Variational Autoencoders with Similarity Learning

Jiahao Huo, Terence L. van Zyl

Catastrophic forgetting in neural networks during incremental learning remains a challenging problem. Previous research investigated catastrophic forgetting in fully connected netw…

cs.CV2020

Unique Faces Recognition in Videos

Jiahao Huo, Terence L van Zyl

This paper tackles face recognition in videos employing metric learning methods and similarity ranking models. The paper compares the use of the Siamese network with contrastive lo…