activity
20162024
most citedReliable Student: Addressing Noise in Semi-Supervised 3D Object Detection

7 citations · 25 across the 12 of their papers we have counts for

collaborators

12 papers

cs.CL2024

ProverbEval: Exploring LLM Evaluation Challenges for Low-resource Language Understanding

Israel Abebe Azime, Atnafu Lambebo Tonja, Tadesse Destaw Belay +11

With the rapid development of evaluation datasets to assess LLMs understanding across a wide range of subjects and domains, identifying a suitable language understanding benchmark…

cs.GR20244 cited

MARS: Multi-sample Allocation through Russian roulette and Splitting

Joshua Meyer, Alexander Rath, Ömercan Yazici +1

Multiple importance sampling (MIS) is an indispensable tool in rendering that constructs robust sampling strategies by combining the respective strengths of individual distribution…

cs.CV20247 cited

Reliable Student: Addressing Noise in Semi-Supervised 3D Object Detection

Farzad Nozarian, Shashank Agarwal, Farzaneh Rezaeianaran +4

Semi-supervised 3D object detection can benefit from the promising pseudo-labeling technique when labeled data is limited. However, recent approaches have overlooked the impact of…

cs.CL2024

What explains the success of cross-modal fine-tuning with ORCA?

Paloma García-de-Herreros, Vagrant Gautam, Philipp Slusallek +2

ORCA (Shen et al., 2023) is a recent technique for cross-modal fine-tuning, i.e., applying pre-trained transformer models to modalities beyond their training data. The technique co…

cs.GR20233 cited

Discovering Fatigued Movements for Virtual Character Animation

Noshaba Cheema, Rui Xu, Nam Hee Kim +5

Virtual character animation and movement synthesis have advanced rapidly during recent years, especially through a combination of extensive motion capture datasets and machine lear…

cs.GR20232 cited

Perceptual error optimization for Monte Carlo animation rendering

Miša Korać, Corentin Salaün, Iliyan Georgiev +4

Independently estimating pixel values in Monte Carlo rendering results in a perceptually sub-optimal white-noise distribution of error in image space. Recent works have shown that…